Released Models

Acoustic Model Released in paddle 2.X

Acoustic Model	Training Data	Token-based	Size	Descriptions	CER	WER	Hours of speech
Ds2 Online Aishell Model	Aishell Dataset	Char-based	345 MB	2 Conv + 5 LSTM layers with only forward direction	0.0824	-	151 h
Ds2 Offline Aishell Model	Aishell Dataset	Char-based	306 MB	2 Conv + 3 bidirectional GRU layers	0.065	-	151 h
Conformer Online Aishell Model	Aishell Dataset	Char-based	283 MB	Encoder:Conformer, Decoder:Transformer, Decoding method: Attention + CTC	0.0594	-	151 h
Conformer Offline Aishell Model	Aishell Dataset	Char-based	284 MB	Encoder:Conformer, Decoder:Transformer, Decoding method: Attention	0.0547	-	151 h
Conformer Librispeech Model	Librispeech Dataset	Word-based	287 MB	Encoder:Conformer, Decoder:Transformer, Decoding method: Attention	-	0.0325	960 h
Transformer Librispeech Model	Librispeech Dataset	Word-based	195 MB	Encoder:Conformer, Decoder:Transformer, Decoding method: Attention	-	0.0544	960 h

Acoustic Model	Training Data	Token-based	Size	Descriptions	CER	WER	Hours of speech
Ds2 Offline Aishell model	Aishell Dataset	Char-based	234 MB	2 Conv + 3 bidirectional GRU layers	0.0804	-	151 h
Ds2 Offline Librispeech model	Librispeech Dataset	Word-based	307 MB	2 Conv + 3 bidirectional sharing weight RNN layers	-	0.0685	960 h
Ds2 Offline Baidu en8k model	Baidu Internal English Dataset	Word-based	273 MB	2 Conv + 3 bidirectional GRU layers	-	0.0541	8628 h

Language Model	Training Data	Token-based	Size	Descriptions
English LM	CommonCrawl(en.00)	Word-based	8.3 GB	Pruned with 0 1 1 1 1; About 1.85 billion n-grams; 'trie' binary with '-a 22 -q 8 -b 8'
Mandarin LM Small	Baidu Internal Corpus	Char-based	2.8 GB	Pruned with 0 1 2 4 4; About 0.13 billion n-grams; 'probing' binary with default settings
Mandarin LM Large	Baidu Internal Corpus	Char-based	70.4 GB	No Pruning; About 3.7 billion n-grams; 'probing' binary with default settings