Hui Zhang
2 years ago
committed by
GitHub
commit
c938a450b0
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# This is the parameter configuration file for PaddleSpeech Serving.
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#################################################################################
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# SERVER SETTING #
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#################################################################################
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host: 0.0.0.0
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port: 8090
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# The task format in the engin_list is: <speech task>_<engine type>
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# task choices = ['asr_online', 'tts_online']
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# protocol = ['websocket', 'http'] (only one can be selected).
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# websocket only support online engine type.
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protocol: 'websocket'
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engine_list: ['asr_online']
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#################################################################################
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# ENGINE CONFIG #
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#################################################################################
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################################### ASR #########################################
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################### speech task: asr; engine_type: online #######################
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asr_online:
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model_type: 'conformer_online_multicn'
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am_model: # the pdmodel file of am static model [optional]
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am_params: # the pdiparams file of am static model [optional]
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lang: 'zh'
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sample_rate: 16000
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cfg_path:
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decode_method:
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force_yes: True
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am_predictor_conf:
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device: # set 'gpu:id' or 'cpu'
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switch_ir_optim: True
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glog_info: False # True -> print glog
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summary: True # False -> do not show predictor config
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chunk_buffer_conf:
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window_n: 7 # frame
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shift_n: 4 # frame
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window_ms: 25 # ms
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shift_ms: 10 # ms
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sample_rate: 16000
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sample_width: 2
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# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from collections import defaultdict
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import paddle
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from paddlespeech.cli.log import logger
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from paddlespeech.s2t.utils.utility import log_add
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__all__ = ['CTCPrefixBeamSearch']
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class CTCPrefixBeamSearch:
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def __init__(self, config):
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"""Implement the ctc prefix beam search
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Args:
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config (yacs.config.CfgNode): _description_
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"""
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self.config = config
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self.reset()
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@paddle.no_grad()
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def search(self, ctc_probs, device, blank_id=0):
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"""ctc prefix beam search method decode a chunk feature
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Args:
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xs (paddle.Tensor): feature data
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ctc_probs (paddle.Tensor): the ctc probability of all the tokens
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device (paddle.fluid.core_avx.Place): the feature host device, such as CUDAPlace(0).
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blank_id (int, optional): the blank id in the vocab. Defaults to 0.
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Returns:
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list: the search result
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"""
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# decode
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logger.info("start to ctc prefix search")
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batch_size = 1
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beam_size = self.config.beam_size
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maxlen = ctc_probs.shape[0]
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assert len(ctc_probs.shape) == 2
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# cur_hyps: (prefix, (blank_ending_score, none_blank_ending_score))
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# blank_ending_score and none_blank_ending_score in ln domain
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if self.cur_hyps is None:
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self.cur_hyps = [(tuple(), (0.0, -float('inf')))]
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# 2. CTC beam search step by step
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for t in range(0, maxlen):
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logp = ctc_probs[t] # (vocab_size,)
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# key: prefix, value (pb, pnb), default value(-inf, -inf)
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next_hyps = defaultdict(lambda: (-float('inf'), -float('inf')))
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# 2.1 First beam prune: select topk best
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# do token passing process
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top_k_logp, top_k_index = logp.topk(beam_size) # (beam_size,)
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for s in top_k_index:
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s = s.item()
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ps = logp[s].item()
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for prefix, (pb, pnb) in self.cur_hyps:
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last = prefix[-1] if len(prefix) > 0 else None
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if s == blank_id: # blank
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n_pb, n_pnb = next_hyps[prefix]
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n_pb = log_add([n_pb, pb + ps, pnb + ps])
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next_hyps[prefix] = (n_pb, n_pnb)
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elif s == last:
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# Update *ss -> *s;
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n_pb, n_pnb = next_hyps[prefix]
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n_pnb = log_add([n_pnb, pnb + ps])
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next_hyps[prefix] = (n_pb, n_pnb)
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# Update *s-s -> *ss, - is for blank
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n_prefix = prefix + (s, )
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n_pb, n_pnb = next_hyps[n_prefix]
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n_pnb = log_add([n_pnb, pb + ps])
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next_hyps[n_prefix] = (n_pb, n_pnb)
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else:
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n_prefix = prefix + (s, )
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n_pb, n_pnb = next_hyps[n_prefix]
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n_pnb = log_add([n_pnb, pb + ps, pnb + ps])
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next_hyps[n_prefix] = (n_pb, n_pnb)
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# 2.2 Second beam prune
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next_hyps = sorted(
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next_hyps.items(),
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key=lambda x: log_add(list(x[1])),
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reverse=True)
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self.cur_hyps = next_hyps[:beam_size]
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self.hyps = [(y[0], log_add([y[1][0], y[1][1]])) for y in self.cur_hyps]
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logger.info("ctc prefix search success")
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return self.hyps
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def get_one_best_hyps(self):
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"""Return the one best result
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Returns:
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list: the one best result
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"""
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return [self.hyps[0][0]]
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def get_hyps(self):
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"""Return the search hyps
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Returns:
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list: return the search hyps
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"""
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return self.hyps
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def reset(self):
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"""Rest the search cache value
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"""
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self.cur_hyps = None
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self.hyps = None
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def finalize_search(self):
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"""do nothing in ctc_prefix_beam_search
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"""
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pass
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# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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@ -0,0 +1,13 @@
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# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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@ -0,0 +1,13 @@
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# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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@ -0,0 +1,13 @@
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# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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@ -0,0 +1,37 @@
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#!/bin/bash
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set +x
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set -e
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. path.sh
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# 1. compile
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if [ ! -d ${SPEECHX_EXAMPLES} ]; then
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pushd ${SPEECHX_ROOT}
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bash build.sh
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popd
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fi
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# input
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mkdir -p data
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data=$PWD/data
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ckpt_dir=$data/model
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model_dir=$ckpt_dir/exp/deepspeech2_online/checkpoints/
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vocb_dir=$ckpt_dir/data/lang_char
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# output
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aishell_wav_scp=aishell_test.scp
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if [ ! -d $data/test ]; then
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pushd $data
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wget -c https://paddlespeech.bj.bcebos.com/s2t/paddle_asr_online/aishell_test.zip
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unzip aishell_test.zip
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popd
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realpath $data/test/*/*.wav > $data/wavlist
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awk -F '/' '{ print $(NF) }' $data/wavlist | awk -F '.' '{ print $1 }' > $data/utt_id
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paste $data/utt_id $data/wavlist > $data/$aishell_wav_scp
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fi
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export GLOG_logtostderr=1
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# websocket client
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websocket_client_main \
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--wav_rspecifier=scp:$data/$aishell_wav_scp --streaming_chunk=0.36
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#!/bin/bash
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set +x
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set -e
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. path.sh
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# 1. compile
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if [ ! -d ${SPEECHX_EXAMPLES} ]; then
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pushd ${SPEECHX_ROOT}
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bash build.sh
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popd
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fi
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# input
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mkdir -p data
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data=$PWD/data
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ckpt_dir=$data/model
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model_dir=$ckpt_dir/exp/deepspeech2_online/checkpoints/
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vocb_dir=$ckpt_dir/data/lang_char/
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# output
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aishell_wav_scp=aishell_test.scp
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if [ ! -d $data/test ]; then
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pushd $data
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wget -c https://paddlespeech.bj.bcebos.com/s2t/paddle_asr_online/aishell_test.zip
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unzip aishell_test.zip
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popd
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realpath $data/test/*/*.wav > $data/wavlist
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awk -F '/' '{ print $(NF) }' $data/wavlist | awk -F '.' '{ print $1 }' > $data/utt_id
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paste $data/utt_id $data/wavlist > $data/$aishell_wav_scp
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fi
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if [ ! -d $ckpt_dir ]; then
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mkdir -p $ckpt_dir
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wget -P $ckpt_dir -c https://paddlespeech.bj.bcebos.com/s2t/aishell/asr0/asr0_deepspeech2_online_aishell_ckpt_0.2.0.model.tar.gz
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tar xzfv $ckpt_dir/asr0_deepspeech2_online_aishell_ckpt_0.2.0.model.tar.gz -C $ckpt_dir
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fi
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export GLOG_logtostderr=1
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# 3. gen cmvn
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cmvn=$PWD/cmvn.ark
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cmvn-json2kaldi --json_file=$ckpt_dir/data/mean_std.json --cmvn_write_path=$cmvn
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text=$data/test/text
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graph_dir=./aishell_graph
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if [ ! -d $graph_dir ]; then
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wget -c https://paddlespeech.bj.bcebos.com/s2t/paddle_asr_online/aishell_graph.zip
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unzip aishell_graph.zip
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fi
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# 5. test websocket server
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websocket_server_main \
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--cmvn_file=$cmvn \
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--model_path=$model_dir/avg_1.jit.pdmodel \
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--streaming_chunk=0.1 \
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--convert2PCM32=true \
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--params_path=$model_dir/avg_1.jit.pdiparams \
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--word_symbol_table=$graph_dir/words.txt \
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--model_output_names=softmax_0.tmp_0,tmp_5,concat_0.tmp_0,concat_1.tmp_0 \
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--graph_path=$graph_dir/TLG.fst --max_active=7500 \
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--acoustic_scale=1.2
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@ -0,0 +1,85 @@
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// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
|
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// You may obtain a copy of the License at
|
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
|
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// distributed under the License is distributed on an "AS IS" BASIS,
|
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
// See the License for the specific language governing permissions and
|
||||
// limitations under the License.
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#include "decoder/recognizer.h"
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#include "decoder/param.h"
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#include "kaldi/feat/wave-reader.h"
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#include "kaldi/util/table-types.h"
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DEFINE_string(wav_rspecifier, "", "test feature rspecifier");
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DEFINE_string(result_wspecifier, "", "test result wspecifier");
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int main(int argc, char* argv[]) {
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gflags::ParseCommandLineFlags(&argc, &argv, false);
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google::InitGoogleLogging(argv[0]);
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ppspeech::RecognizerResource resource = ppspeech::InitRecognizerResoure();
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ppspeech::Recognizer recognizer(resource);
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kaldi::SequentialTableReader<kaldi::WaveHolder> wav_reader(
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FLAGS_wav_rspecifier);
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kaldi::TokenWriter result_writer(FLAGS_result_wspecifier);
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int sample_rate = 16000;
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float streaming_chunk = FLAGS_streaming_chunk;
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int chunk_sample_size = streaming_chunk * sample_rate;
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LOG(INFO) << "sr: " << sample_rate;
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LOG(INFO) << "chunk size (s): " << streaming_chunk;
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LOG(INFO) << "chunk size (sample): " << chunk_sample_size;
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int32 num_done = 0, num_err = 0;
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for (; !wav_reader.Done(); wav_reader.Next()) {
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std::string utt = wav_reader.Key();
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const kaldi::WaveData& wave_data = wav_reader.Value();
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int32 this_channel = 0;
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kaldi::SubVector<kaldi::BaseFloat> waveform(wave_data.Data(),
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this_channel);
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int tot_samples = waveform.Dim();
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LOG(INFO) << "wav len (sample): " << tot_samples;
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int sample_offset = 0;
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std::vector<kaldi::Vector<BaseFloat>> feats;
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int feature_rows = 0;
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while (sample_offset < tot_samples) {
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int cur_chunk_size =
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std::min(chunk_sample_size, tot_samples - sample_offset);
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kaldi::Vector<kaldi::BaseFloat> wav_chunk(cur_chunk_size);
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for (int i = 0; i < cur_chunk_size; ++i) {
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wav_chunk(i) = waveform(sample_offset + i);
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}
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recognizer.Accept(wav_chunk);
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if (cur_chunk_size < chunk_sample_size) {
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recognizer.SetFinished();
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}
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recognizer.Decode();
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sample_offset += cur_chunk_size;
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}
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std::string result;
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result = recognizer.GetFinalResult();
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recognizer.Reset();
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if (result.empty()) {
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// the TokenWriter can not write empty string.
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++num_err;
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KALDI_LOG << " the result of " << utt << " is empty";
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continue;
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}
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KALDI_LOG << " the result of " << utt << " is " << result;
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result_writer.Write(utt, result);
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++num_done;
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}
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}
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@ -0,0 +1,10 @@
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cmake_minimum_required(VERSION 3.14 FATAL_ERROR)
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add_executable(websocket_server_main ${CMAKE_CURRENT_SOURCE_DIR}/websocket_server_main.cc)
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target_include_directories(websocket_server_main PRIVATE ${SPEECHX_ROOT} ${SPEECHX_ROOT}/kaldi)
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target_link_libraries(websocket_server_main PUBLIC frontend kaldi-feat-common nnet decoder fst utils gflags glog kaldi-base kaldi-matrix kaldi-util kaldi-decoder websocket ${DEPS})
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add_executable(websocket_client_main ${CMAKE_CURRENT_SOURCE_DIR}/websocket_client_main.cc)
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target_include_directories(websocket_client_main PRIVATE ${SPEECHX_ROOT} ${SPEECHX_ROOT}/kaldi)
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target_link_libraries(websocket_client_main PUBLIC frontend kaldi-feat-common nnet decoder fst utils gflags glog kaldi-base kaldi-matrix kaldi-util kaldi-decoder websocket ${DEPS})
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@ -0,0 +1,82 @@
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// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
|
||||
//
|
||||
// Licensed under the Apache License, Version 2.0 (the "License");
|
||||
// you may not use this file except in compliance with the License.
|
||||
// You may obtain a copy of the License at
|
||||
//
|
||||
// http://www.apache.org/licenses/LICENSE-2.0
|
||||
//
|
||||
// Unless required by applicable law or agreed to in writing, software
|
||||
// distributed under the License is distributed on an "AS IS" BASIS,
|
||||
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
// See the License for the specific language governing permissions and
|
||||
// limitations under the License.
|
||||
|
||||
#include "websocket/websocket_client.h"
|
||||
#include "kaldi/feat/wave-reader.h"
|
||||
#include "kaldi/util/kaldi-io.h"
|
||||
#include "kaldi/util/table-types.h"
|
||||
|
||||
DEFINE_string(host, "127.0.0.1", "host of websocket server");
|
||||
DEFINE_int32(port, 201314, "port of websocket server");
|
||||
DEFINE_string(wav_rspecifier, "", "test wav scp path");
|
||||
DEFINE_double(streaming_chunk, 0.1, "streaming feature chunk size");
|
||||
|
||||
using kaldi::int16;
|
||||
int main(int argc, char* argv[]) {
|
||||
gflags::ParseCommandLineFlags(&argc, &argv, false);
|
||||
google::InitGoogleLogging(argv[0]);
|
||||
ppspeech::WebSocketClient client(FLAGS_host, FLAGS_port);
|
||||
|
||||
kaldi::SequentialTableReader<kaldi::WaveHolder> wav_reader(
|
||||
FLAGS_wav_rspecifier);
|
||||
|
||||
const int sample_rate = 16000;
|
||||
const float streaming_chunk = FLAGS_streaming_chunk;
|
||||
const int chunk_sample_size = streaming_chunk * sample_rate;
|
||||
|
||||
for (; !wav_reader.Done(); wav_reader.Next()) {
|
||||
client.SendStartSignal();
|
||||
std::string utt = wav_reader.Key();
|
||||
const kaldi::WaveData& wave_data = wav_reader.Value();
|
||||
CHECK_EQ(wave_data.SampFreq(), sample_rate);
|
||||
|
||||
int32 this_channel = 0;
|
||||
kaldi::SubVector<kaldi::BaseFloat> waveform(wave_data.Data(),
|
||||
this_channel);
|
||||
const int tot_samples = waveform.Dim();
|
||||
int sample_offset = 0;
|
||||
|
||||
while (sample_offset < tot_samples) {
|
||||
int cur_chunk_size =
|
||||
std::min(chunk_sample_size, tot_samples - sample_offset);
|
||||
|
||||
std::vector<int16> wav_chunk(cur_chunk_size);
|
||||
for (int i = 0; i < cur_chunk_size; ++i) {
|
||||
wav_chunk[i] = static_cast<int16>(waveform(sample_offset + i));
|
||||
}
|
||||
client.SendBinaryData(wav_chunk.data(),
|
||||
wav_chunk.size() * sizeof(int16));
|
||||
|
||||
|
||||
sample_offset += cur_chunk_size;
|
||||
LOG(INFO) << "Send " << cur_chunk_size << " samples";
|
||||
std::this_thread::sleep_for(
|
||||
std::chrono::milliseconds(static_cast<int>(1 * 1000)));
|
||||
|
||||
if (cur_chunk_size < chunk_sample_size) {
|
||||
client.SendEndSignal();
|
||||
}
|
||||
}
|
||||
|
||||
while (!client.Done()) {
|
||||
}
|
||||
std::string result = client.GetResult();
|
||||
LOG(INFO) << "utt: " << utt << " " << result;
|
||||
|
||||
|
||||
client.Join();
|
||||
return 0;
|
||||
}
|
||||
return 0;
|
||||
}
|
||||
@ -0,0 +1,30 @@
|
||||
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
|
||||
//
|
||||
// Licensed under the Apache License, Version 2.0 (the "License");
|
||||
// you may not use this file except in compliance with the License.
|
||||
// You may obtain a copy of the License at
|
||||
//
|
||||
// http://www.apache.org/licenses/LICENSE-2.0
|
||||
//
|
||||
// Unless required by applicable law or agreed to in writing, software
|
||||
// distributed under the License is distributed on an "AS IS" BASIS,
|
||||
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
// See the License for the specific language governing permissions and
|
||||
// limitations under the License.
|
||||
|
||||
#include "websocket/websocket_server.h"
|
||||
#include "decoder/param.h"
|
||||
|
||||
DEFINE_int32(port, 201314, "websocket listening port");
|
||||
|
||||
int main(int argc, char *argv[]) {
|
||||
gflags::ParseCommandLineFlags(&argc, &argv, false);
|
||||
google::InitGoogleLogging(argv[0]);
|
||||
|
||||
ppspeech::RecognizerResource resource = ppspeech::InitRecognizerResoure();
|
||||
|
||||
ppspeech::WebSocketServer server(FLAGS_port, resource);
|
||||
LOG(INFO) << "Listening at port " << FLAGS_port;
|
||||
server.Start();
|
||||
return 0;
|
||||
}
|
||||
@ -0,0 +1,94 @@
|
||||
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
|
||||
//
|
||||
// Licensed under the Apache License, Version 2.0 (the "License");
|
||||
// you may not use this file except in compliance with the License.
|
||||
// You may obtain a copy of the License at
|
||||
//
|
||||
// http://www.apache.org/licenses/LICENSE-2.0
|
||||
//
|
||||
// Unless required by applicable law or agreed to in writing, software
|
||||
// distributed under the License is distributed on an "AS IS" BASIS,
|
||||
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
// See the License for the specific language governing permissions and
|
||||
// limitations under the License.
|
||||
|
||||
#pragma once
|
||||
|
||||
#include "base/common.h"
|
||||
|
||||
#include "decoder/ctc_beam_search_decoder.h"
|
||||
#include "decoder/ctc_tlg_decoder.h"
|
||||
#include "frontend/audio/feature_pipeline.h"
|
||||
|
||||
DEFINE_string(cmvn_file, "", "read cmvn");
|
||||
DEFINE_double(streaming_chunk, 0.1, "streaming feature chunk size");
|
||||
DEFINE_bool(convert2PCM32, true, "audio convert to pcm32");
|
||||
DEFINE_string(model_path, "avg_1.jit.pdmodel", "paddle nnet model");
|
||||
DEFINE_string(params_path, "avg_1.jit.pdiparams", "paddle nnet model param");
|
||||
DEFINE_string(word_symbol_table, "words.txt", "word symbol table");
|
||||
DEFINE_string(graph_path, "TLG", "decoder graph");
|
||||
DEFINE_double(acoustic_scale, 1.0, "acoustic scale");
|
||||
DEFINE_int32(max_active, 7500, "max active");
|
||||
DEFINE_double(beam, 15.0, "decoder beam");
|
||||
DEFINE_double(lattice_beam, 7.5, "decoder beam");
|
||||
DEFINE_int32(receptive_field_length,
|
||||
7,
|
||||
"receptive field of two CNN(kernel=5) downsampling module.");
|
||||
DEFINE_int32(downsampling_rate,
|
||||
4,
|
||||
"two CNN(kernel=5) module downsampling rate.");
|
||||
DEFINE_string(model_output_names,
|
||||
"save_infer_model/scale_0.tmp_1,save_infer_model/"
|
||||
"scale_1.tmp_1,save_infer_model/scale_2.tmp_1,save_infer_model/"
|
||||
"scale_3.tmp_1",
|
||||
"model output names");
|
||||
DEFINE_string(model_cache_names, "5-1-1024,5-1-1024", "model cache names");
|
||||
|
||||
namespace ppspeech {
|
||||
// todo refactor later
|
||||
FeaturePipelineOptions InitFeaturePipelineOptions() {
|
||||
FeaturePipelineOptions opts;
|
||||
opts.cmvn_file = FLAGS_cmvn_file;
|
||||
opts.linear_spectrogram_opts.streaming_chunk = FLAGS_streaming_chunk;
|
||||
opts.convert2PCM32 = FLAGS_convert2PCM32;
|
||||
kaldi::FrameExtractionOptions frame_opts;
|
||||
frame_opts.frame_length_ms = 20;
|
||||
frame_opts.frame_shift_ms = 10;
|
||||
frame_opts.remove_dc_offset = false;
|
||||
frame_opts.window_type = "hanning";
|
||||
frame_opts.preemph_coeff = 0.0;
|
||||
frame_opts.dither = 0.0;
|
||||
opts.linear_spectrogram_opts.frame_opts = frame_opts;
|
||||
opts.feature_cache_opts.frame_chunk_size = FLAGS_receptive_field_length;
|
||||
opts.feature_cache_opts.frame_chunk_stride = FLAGS_downsampling_rate;
|
||||
return opts;
|
||||
}
|
||||
|
||||
ModelOptions InitModelOptions() {
|
||||
ModelOptions model_opts;
|
||||
model_opts.model_path = FLAGS_model_path;
|
||||
model_opts.params_path = FLAGS_params_path;
|
||||
model_opts.cache_shape = FLAGS_model_cache_names;
|
||||
model_opts.output_names = FLAGS_model_output_names;
|
||||
return model_opts;
|
||||
}
|
||||
|
||||
TLGDecoderOptions InitDecoderOptions() {
|
||||
TLGDecoderOptions decoder_opts;
|
||||
decoder_opts.word_symbol_table = FLAGS_word_symbol_table;
|
||||
decoder_opts.fst_path = FLAGS_graph_path;
|
||||
decoder_opts.opts.max_active = FLAGS_max_active;
|
||||
decoder_opts.opts.beam = FLAGS_beam;
|
||||
decoder_opts.opts.lattice_beam = FLAGS_lattice_beam;
|
||||
return decoder_opts;
|
||||
}
|
||||
|
||||
RecognizerResource InitRecognizerResoure() {
|
||||
RecognizerResource resource;
|
||||
resource.acoustic_scale = FLAGS_acoustic_scale;
|
||||
resource.feature_pipeline_opts = InitFeaturePipelineOptions();
|
||||
resource.model_opts = InitModelOptions();
|
||||
resource.tlg_opts = InitDecoderOptions();
|
||||
return resource;
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,60 @@
|
||||
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
|
||||
//
|
||||
// Licensed under the Apache License, Version 2.0 (the "License");
|
||||
// you may not use this file except in compliance with the License.
|
||||
// You may obtain a copy of the License at
|
||||
//
|
||||
// http://www.apache.org/licenses/LICENSE-2.0
|
||||
//
|
||||
// Unless required by applicable law or agreed to in writing, software
|
||||
// distributed under the License is distributed on an "AS IS" BASIS,
|
||||
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
// See the License for the specific language governing permissions and
|
||||
// limitations under the License.
|
||||
|
||||
#include "decoder/recognizer.h"
|
||||
|
||||
namespace ppspeech {
|
||||
|
||||
using kaldi::Vector;
|
||||
using kaldi::VectorBase;
|
||||
using kaldi::BaseFloat;
|
||||
using std::vector;
|
||||
using kaldi::SubVector;
|
||||
using std::unique_ptr;
|
||||
|
||||
Recognizer::Recognizer(const RecognizerResource& resource) {
|
||||
// resource_ = resource;
|
||||
const FeaturePipelineOptions& feature_opts = resource.feature_pipeline_opts;
|
||||
feature_pipeline_.reset(new FeaturePipeline(feature_opts));
|
||||
std::shared_ptr<PaddleNnet> nnet(new PaddleNnet(resource.model_opts));
|
||||
BaseFloat ac_scale = resource.acoustic_scale;
|
||||
decodable_.reset(new Decodable(nnet, feature_pipeline_, ac_scale));
|
||||
decoder_.reset(new TLGDecoder(resource.tlg_opts));
|
||||
input_finished_ = false;
|
||||
}
|
||||
|
||||
void Recognizer::Accept(const Vector<BaseFloat>& waves) {
|
||||
feature_pipeline_->Accept(waves);
|
||||
}
|
||||
|
||||
void Recognizer::Decode() { decoder_->AdvanceDecode(decodable_); }
|
||||
|
||||
std::string Recognizer::GetFinalResult() {
|
||||
return decoder_->GetFinalBestPath();
|
||||
}
|
||||
|
||||
void Recognizer::SetFinished() {
|
||||
feature_pipeline_->SetFinished();
|
||||
input_finished_ = true;
|
||||
}
|
||||
|
||||
bool Recognizer::IsFinished() { return input_finished_; }
|
||||
|
||||
void Recognizer::Reset() {
|
||||
feature_pipeline_->Reset();
|
||||
decodable_->Reset();
|
||||
decoder_->Reset();
|
||||
}
|
||||
|
||||
} // namespace ppspeech
|
||||
@ -0,0 +1,59 @@
|
||||
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
|
||||
//
|
||||
// Licensed under the Apache License, Version 2.0 (the "License");
|
||||
// you may not use this file except in compliance with the License.
|
||||
// You may obtain a copy of the License at
|
||||
//
|
||||
// http://www.apache.org/licenses/LICENSE-2.0
|
||||
//
|
||||
// Unless required by applicable law or agreed to in writing, software
|
||||
// distributed under the License is distributed on an "AS IS" BASIS,
|
||||
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
// See the License for the specific language governing permissions and
|
||||
// limitations under the License.
|
||||
|
||||
// todo refactor later (SGoat)
|
||||
|
||||
#pragma once
|
||||
|
||||
#include "decoder/ctc_beam_search_decoder.h"
|
||||
#include "decoder/ctc_tlg_decoder.h"
|
||||
#include "frontend/audio/feature_pipeline.h"
|
||||
#include "nnet/decodable.h"
|
||||
#include "nnet/paddle_nnet.h"
|
||||
|
||||
namespace ppspeech {
|
||||
|
||||
struct RecognizerResource {
|
||||
FeaturePipelineOptions feature_pipeline_opts;
|
||||
ModelOptions model_opts;
|
||||
TLGDecoderOptions tlg_opts;
|
||||
// CTCBeamSearchOptions beam_search_opts;
|
||||
kaldi::BaseFloat acoustic_scale;
|
||||
RecognizerResource()
|
||||
: acoustic_scale(1.0),
|
||||
feature_pipeline_opts(),
|
||||
model_opts(),
|
||||
tlg_opts() {}
|
||||
};
|
||||
|
||||
class Recognizer {
|
||||
public:
|
||||
explicit Recognizer(const RecognizerResource& resouce);
|
||||
void Accept(const kaldi::Vector<kaldi::BaseFloat>& waves);
|
||||
void Decode();
|
||||
std::string GetFinalResult();
|
||||
void SetFinished();
|
||||
bool IsFinished();
|
||||
void Reset();
|
||||
|
||||
private:
|
||||
// std::shared_ptr<RecognizerResource> resource_;
|
||||
// RecognizerResource resource_;
|
||||
std::shared_ptr<FeaturePipeline> feature_pipeline_;
|
||||
std::shared_ptr<Decodable> decodable_;
|
||||
std::unique_ptr<TLGDecoder> decoder_;
|
||||
bool input_finished_;
|
||||
};
|
||||
|
||||
} // namespace ppspeech
|
||||
@ -0,0 +1,36 @@
|
||||
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
|
||||
//
|
||||
// Licensed under the Apache License, Version 2.0 (the "License");
|
||||
// you may not use this file except in compliance with the License.
|
||||
// You may obtain a copy of the License at
|
||||
//
|
||||
// http://www.apache.org/licenses/LICENSE-2.0
|
||||
//
|
||||
// Unless required by applicable law or agreed to in writing, software
|
||||
// distributed under the License is distributed on an "AS IS" BASIS,
|
||||
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
// See the License for the specific language governing permissions and
|
||||
// limitations under the License.
|
||||
|
||||
#include "frontend/audio/feature_pipeline.h"
|
||||
|
||||
namespace ppspeech {
|
||||
|
||||
using std::unique_ptr;
|
||||
|
||||
FeaturePipeline::FeaturePipeline(const FeaturePipelineOptions& opts) {
|
||||
unique_ptr<FrontendInterface> data_source(
|
||||
new ppspeech::AudioCache(1000 * kint16max, opts.convert2PCM32));
|
||||
|
||||
unique_ptr<FrontendInterface> linear_spectrogram(
|
||||
new ppspeech::LinearSpectrogram(opts.linear_spectrogram_opts,
|
||||
std::move(data_source)));
|
||||
|
||||
unique_ptr<FrontendInterface> cmvn(
|
||||
new ppspeech::CMVN(opts.cmvn_file, std::move(linear_spectrogram)));
|
||||
|
||||
base_extractor_.reset(
|
||||
new ppspeech::FeatureCache(opts.feature_cache_opts, std::move(cmvn)));
|
||||
}
|
||||
|
||||
} // ppspeech
|
||||
@ -0,0 +1,57 @@
|
||||
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
|
||||
//
|
||||
// Licensed under the Apache License, Version 2.0 (the "License");
|
||||
// you may not use this file except in compliance with the License.
|
||||
// You may obtain a copy of the License at
|
||||
//
|
||||
// http://www.apache.org/licenses/LICENSE-2.0
|
||||
//
|
||||
// Unless required by applicable law or agreed to in writing, software
|
||||
// distributed under the License is distributed on an "AS IS" BASIS,
|
||||
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
// See the License for the specific language governing permissions and
|
||||
// limitations under the License.
|
||||
|
||||
// todo refactor later (SGoat)
|
||||
|
||||
#pragma once
|
||||
|
||||
#include "frontend/audio/audio_cache.h"
|
||||
#include "frontend/audio/data_cache.h"
|
||||
#include "frontend/audio/feature_cache.h"
|
||||
#include "frontend/audio/frontend_itf.h"
|
||||
#include "frontend/audio/linear_spectrogram.h"
|
||||
#include "frontend/audio/normalizer.h"
|
||||
|
||||
namespace ppspeech {
|
||||
|
||||
struct FeaturePipelineOptions {
|
||||
std::string cmvn_file;
|
||||
bool convert2PCM32;
|
||||
LinearSpectrogramOptions linear_spectrogram_opts;
|
||||
FeatureCacheOptions feature_cache_opts;
|
||||
FeaturePipelineOptions()
|
||||
: cmvn_file(""),
|
||||
convert2PCM32(false),
|
||||
linear_spectrogram_opts(),
|
||||
feature_cache_opts() {}
|
||||
};
|
||||
|
||||
class FeaturePipeline : public FrontendInterface {
|
||||
public:
|
||||
explicit FeaturePipeline(const FeaturePipelineOptions& opts);
|
||||
virtual void Accept(const kaldi::VectorBase<kaldi::BaseFloat>& waves) {
|
||||
base_extractor_->Accept(waves);
|
||||
}
|
||||
virtual bool Read(kaldi::Vector<kaldi::BaseFloat>* feats) {
|
||||
return base_extractor_->Read(feats);
|
||||
}
|
||||
virtual size_t Dim() const { return base_extractor_->Dim(); }
|
||||
virtual void SetFinished() { base_extractor_->SetFinished(); }
|
||||
virtual bool IsFinished() const { return base_extractor_->IsFinished(); }
|
||||
virtual void Reset() { base_extractor_->Reset(); }
|
||||
|
||||
private:
|
||||
std::unique_ptr<FrontendInterface> base_extractor_;
|
||||
};
|
||||
}
|
||||
Loading…
Reference in new issue