diff --git a/docs/source/released_model.md b/docs/source/released_model.md index 82cd02d111aa768a3e3b9e5ba6a3cda05a57b4f7..367b7c4b88a8674c4f797edd711a6dfe739fa411 100644 --- a/docs/source/released_model.md +++ b/docs/source/released_model.md @@ -1,6 +1,7 @@ # Released Models ## Speech-to-Text Models + ### Acoustic Model Released in paddle 2.X Acoustic Model | Training Data | Token-based | Size | Descriptions | CER | WER | Hours of speech | example link :-------------:| :------------:| :-----: | -----: | :----------------- |:--------- | :---------- | :--------- | :----------- @@ -9,8 +10,9 @@ Acoustic Model | Training Data | Token-based | Size | Descriptions | CER | WER | [Conformer Online Aishell ASR1 Model](https://deepspeech.bj.bcebos.com/release2.1/aishell/s1/aishell.chunk.release.tar.gz) | Aishell Dataset | Char-based | 283 MB | Encoder:Conformer, Decoder:Transformer, Decoding method: Attention rescoring | 0.0594 |-| 151 h | [Conformer Online Aishell S1 Example](../../examples/aishell/s1) [Conformer Offline Aishell ASR1 Model](https://deepspeech.bj.bcebos.com/release2.1/aishell/s1/aishell.release.tar.gz) | Aishell Dataset | Char-based | 284 MB | Encoder:Conformer, Decoder:Transformer, Decoding method: Attention rescoring | 0.0547 |-| 151 h | [Conformer Offline Aishell S1 Example](../../examples/aishell/s1) [Conformer Librispeech ASR1 Model](https://deepspeech.bj.bcebos.com/release2.1/librispeech/s1/conformer.release.tar.gz) | Librispeech Dataset | subword-based | 287 MB | Encoder:Conformer, Decoder:Transformer, Decoding method: Attention rescoring |-| 0.0325 | 960 h | [Conformer Librispeech S1 example](../../example/librispeech/s1) -[Transformer Librispeech ASR1 Model](https://deepspeech.bj.bcebos.com/release2.2/librispeech/s1/librispeech.s1.transformer.all.wer5p62.release.tar.gz) | Librispeech Dataset | subword-based | 131 MB | Encoder:Transformer, Decoder:Transformer, Decoding method: Attention rescoring |-| 0.0456 | 960 h | [Transformer Librispeech S1 example](../../example/librispeech/s1) -[Transformer Librispeech ASR2 Model](https://deepspeech.bj.bcebos.com/release2.2/librispeech/s2/libri_transformer_espnet_wer3p84.release.tar.gz) | Librispeech Dataset | subword-based | 131 MB | Encoder:Transformer, Decoder:Transformer, Decoding method: Attention |-| 0.0384 | 960 h | [Transformer Librispeech S2 example](../../example/librispeech/s2) +[Transformer Librispeech ASR1 Model](https://paddlespeech.bj.bcebos.com/s2t/librispeech/asr1/transformer.model.tar.gz) | Librispeech Dataset | subword-based | 131 MB | Encoder:Transformer, Decoder:Transformer, Decoding method: Attention rescoring |-| 0.0410 | 960 h | [Transformer Librispeech S1 example](../../example/librispeech/s1) +[Transformer Librispeech ASR2 Model](https://paddlespeech.bj.bcebos.com/s2t/librispeech/asr2/transformer.model.tar.gz) | Librispeech Dataset | subword-based | 131 MB | Encoder:Transformer, Decoder:Transformer, Decoding method: JoinCTC w/ LM |-| 0.024 | 960 h | [Transformer Librispeech S2 example](../../example/librispeech/s2) + ### Acoustic Model Transformed from paddle 1.8 Acoustic Model | Training Data | Token-based | Size | Descriptions | CER | WER | Hours of speech @@ -20,14 +22,15 @@ Acoustic Model | Training Data | Token-based | Size | Descriptions | CER | WER | [Ds2 Offline Baidu en8k model](https://deepspeech.bj.bcebos.com/eng_models/baidu_en8k_v1.8_to_v2.x.tar.gz)|Baidu Internal English Dataset| Word-based| 273 MB| 2 Conv + 3 bidirectional GRU layers |-| 0.0541 | 8628 h| ### Language Model Released - Language Model | Training Data | Token-based | Size | Descriptions :-------------:| :------------:| :-----: | -----: | :----------------- [English LM](https://deepspeech.bj.bcebos.com/en_lm/common_crawl_00.prune01111.trie.klm) | [CommonCrawl(en.00)](http://web-language-models.s3-website-us-east-1.amazonaws.com/ngrams/en/deduped/en.00.deduped.xz) | 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](https://deepspeech.bj.bcebos.com/zh_lm/zh_giga.no_cna_cmn.prune01244.klm) | 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](https://deepspeech.bj.bcebos.com/zh_lm/zhidao_giga.klm) | Baidu Internal Corpus | Char-based | 70.4 GB | No Pruning;
About 3.7 billion n-grams;
'probing' binary with default settings + ## Text-to-Speech Models + ### Acoustic Models Model Type | Dataset| Example Link | Pretrained Models|Static Models|Siize(static) :-------------:| :------------:| :-----: | :-----:| :-----:| :-----: @@ -40,7 +43,6 @@ FastSpeech2| LJSpeech |[fastspeech2-ljspeech](https://github.com/PaddlePaddle/Pa FastSpeech2| VCTK |[fastspeech2-csmsc](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/vctk/tts3)|[fastspeech2_nosil_vctk_ckpt_0.5.zip](https://paddlespeech.bj.bcebos.com/Parakeet/released_models/fastspeech2/fastspeech2_nosil_vctk_ckpt_0.5.zip)||| ### Vocoders - Model Type | Dataset| Example Link | Pretrained Models| Static Models|Size(static) :-------------:| :------------:| :-----: | :-----:| :-----:| :-----: WaveFlow| LJSpeech |[waveflow-ljspeech](https://github.com/PaddlePaddle/PaddleSpeech/tree/develop/examples/ljspeech/voc0)|[waveflow_ljspeech_ckpt_0.3.zip](https://paddlespeech.bj.bcebos.com/Parakeet/released_models/waveflow/waveflow_ljspeech_ckpt_0.3.zip)||| diff --git a/docs/topic/ctc/ctc_loss.ipynb b/docs/topic/ctc/ctc_loss.ipynb index c0da1f3230cec8961e6b2ff6d7fb431c3cec6bb9..081a6388519d2087b432b51d073e7d492f4b097a 100644 --- a/docs/topic/ctc/ctc_loss.ipynb +++ b/docs/topic/ctc/ctc_loss.ipynb @@ -343,6 +343,16 @@ " $$" ] }, + { + "cell_type": "markdown", + "id": "41637c03", + "metadata": {}, + "source": [ + "## Source Code\n", + "本人在 [warp-ctc](https://github.com/zh794390558/warp-ctc) 上加了注释，并调整 index 的索引方式，便于理解代码。\n", + "对比上面的公式推导和lattice图可以快速理解 ctc 实现。" + ] + }, { "cell_type": "markdown", "id": "coordinated-music", @@ -372,7 +382,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -386,7 +396,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.1" + "version": "3.7.0" }, "toc": { "base_numbering": 1, diff --git a/examples/librispeech/asr1/RESULTS.md b/examples/librispeech/asr1/RESULTS.md index 2ea55fc90f7345a27fd46a850a8d8ddf24be30e9..19300adea6fb3bdf2743956209aa64268f2f1b3c 100644 --- a/examples/librispeech/asr1/RESULTS.md +++ b/examples/librispeech/asr1/RESULTS.md @@ -21,7 +21,7 @@ ## Transformer | Model | Params | Config | Augmentation| Test set | Decode method | Loss | WER | | --- | --- | --- | --- | --- | --- | --- | --- | -| transformer | 32.52 M | conf/transformer.yaml | spec_aug | test-clean | attention | 6.733129533131917 | 0.047874 | -| transformer | 32.52 M | conf/transformer.yaml | spec_aug | test-clean | ctc_greedy_search | 6.733129533131917 | 0.053922 | -| transformer | 32.52 M | conf/transformer.yaml | spec_aug | test-clean | ctc_prefix_beam_search | 6.733129533131917 | 0.053427 | -| transformer | 32.52 M | conf/transformer.yaml | spec_aug | test-clean | attention_rescoring | 6.733129533131917 | 0.041369 | +| transformer | 32.52 M | conf/transformer.yaml | spec_aug | test-clean | attention | 6.725063021977743 | 0.047417 | +| transformer | 32.52 M | conf/transformer.yaml | spec_aug | test-clean | ctc_greedy_search | 6.725063021977743 | 0.053922 | +| transformer | 32.52 M | conf/transformer.yaml | spec_aug | test-clean | ctc_prefix_beam_search | 6.725063021977743 | 0.053180 | +| transformer | 32.52 M | conf/transformer.yaml | spec_aug | test-clean | attention_rescoring | 6.725063021977743 | 0.041026 | \ No newline at end of file