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108 lines
4.2 KiB
108 lines
4.2 KiB
#pragma once
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#include "decoder/ctc_beam_search_opt.h"
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#include "decoder/ctc_tlg_decoder.h"
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#include "frontend/feature_pipeline.h"
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DECLARE_int32(nnet_decoder_chunk);
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DECLARE_int32(num_left_chunks);
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DECLARE_double(ctc_weight);
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DECLARE_double(rescoring_weight);
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DECLARE_double(reverse_weight);
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DECLARE_int32(nbest);
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DECLARE_int32(blank);
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DECLARE_double(acoustic_scale);
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DECLARE_double(blank_threshold);
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DECLARE_string(word_symbol_table);
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namespace ppspeech {
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struct DecodeOptions {
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// chunk_size is the frame number of one chunk after subsampling.
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// e.g. if subsample rate is 4 and chunk_size = 16, the frames in
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// one chunk are 67=16*4 + 3, stride is 64=16*4
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int chunk_size{16};
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int num_left_chunks{-1};
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// final_score = rescoring_weight * rescoring_score + ctc_weight *
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// ctc_score;
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// rescoring_score = left_to_right_score * (1 - reverse_weight) +
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// right_to_left_score * reverse_weight
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// Please note the concept of ctc_scores
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// in the following two search methods are different. For
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// CtcPrefixBeamSerch,
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// it's a sum(prefix) score + context score For CtcWfstBeamSerch, it's a
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// max(viterbi) path score + context score So we should carefully set
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// ctc_weight accroding to the search methods.
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float ctc_weight{0.0};
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float rescoring_weight{1.0};
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float reverse_weight{0.0};
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// CtcEndpointConfig ctc_endpoint_opts;
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CTCBeamSearchOptions ctc_prefix_search_opts{};
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TLGDecoderOptions tlg_decoder_opts{};
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static DecodeOptions InitFromFlags() {
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DecodeOptions decoder_opts;
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decoder_opts.chunk_size = FLAGS_nnet_decoder_chunk;
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decoder_opts.num_left_chunks = FLAGS_num_left_chunks;
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decoder_opts.ctc_weight = FLAGS_ctc_weight;
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decoder_opts.rescoring_weight = FLAGS_rescoring_weight;
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decoder_opts.reverse_weight = FLAGS_reverse_weight;
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decoder_opts.ctc_prefix_search_opts.blank = FLAGS_blank;
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decoder_opts.ctc_prefix_search_opts.first_beam_size = FLAGS_nbest;
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decoder_opts.ctc_prefix_search_opts.second_beam_size = FLAGS_nbest;
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decoder_opts.ctc_prefix_search_opts.word_symbol_table =
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FLAGS_word_symbol_table;
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decoder_opts.tlg_decoder_opts =
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ppspeech::TLGDecoderOptions::InitFromFlags();
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LOG(INFO) << "chunk_size: " << decoder_opts.chunk_size;
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LOG(INFO) << "num_left_chunks: " << decoder_opts.num_left_chunks;
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LOG(INFO) << "ctc_weight: " << decoder_opts.ctc_weight;
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LOG(INFO) << "rescoring_weight: " << decoder_opts.rescoring_weight;
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LOG(INFO) << "reverse_weight: " << decoder_opts.reverse_weight;
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LOG(INFO) << "blank: " << FLAGS_blank;
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LOG(INFO) << "first_beam_size: " << FLAGS_nbest;
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LOG(INFO) << "second_beam_size: " << FLAGS_nbest;
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return decoder_opts;
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}
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};
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struct RecognizerResource {
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// decodable opt
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kaldi::BaseFloat acoustic_scale{1.0};
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kaldi::BaseFloat blank_threshold{0.98};
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FeaturePipelineOptions feature_pipeline_opts{};
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ModelOptions model_opts{};
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DecodeOptions decoder_opts{};
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std::shared_ptr<NnetBase> nnet;
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static RecognizerResource InitFromFlags() {
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RecognizerResource resource;
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resource.acoustic_scale = FLAGS_acoustic_scale;
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resource.blank_threshold = FLAGS_blank_threshold;
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LOG(INFO) << "acoustic_scale: " << resource.acoustic_scale;
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resource.feature_pipeline_opts =
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ppspeech::FeaturePipelineOptions::InitFromFlags();
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resource.feature_pipeline_opts.assembler_opts.fill_zero = false;
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LOG(INFO) << "u2 need fill zero be false: "
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<< resource.feature_pipeline_opts.assembler_opts.fill_zero;
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resource.model_opts = ppspeech::ModelOptions::InitFromFlags();
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resource.decoder_opts = ppspeech::DecodeOptions::InitFromFlags();
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#ifndef USE_ONNX
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resource.nnet.reset(new U2Nnet(resource.model_opts));
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#else
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if (resource.model_opts.with_onnx_model){
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resource.nnet.reset(new U2OnnxNnet(resource.model_opts));
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} else {
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resource.nnet.reset(new U2Nnet(resource.model_opts));
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}
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#endif
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return resource;
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}
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};
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} //namespace ppspeech
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