5df24c1685
* add whisper fbank for wenetspeech * add whisper fbank for other dataset * add str to bool * add decode for wenetspeech * add requirments.txt * add original model decode with 30s * test feature extractor speed * add aishell2 feat * change compute feature batch * fix overwrite * fix executor * regression * add kaldifeatwhisper fbank * fix io issue * parallel jobs * use multi machines * add wenetspeech fine-tune scripts * add monkey patch codes * remove useless file * fix subsampling factor * fix too long audios * add remove long short * fix whisper version to support multi batch beam * decode all wav files * remove utterance more than 30s in test_net * only test net * using soft links * add kespeech whisper feats * fix index error * add manifests for whisper * change to licomchunky writer * add missing option * decrease cpu usage * add speed perturb for kespeech * fix kespeech speed perturb * add dataset * load checkpoint from specific path * add speechio * add speechio results --------- Co-authored-by: zr_jin <peter.jin.cn@gmail.com>
Introduction
This recipe contains various different ASR models trained with Aishell2.
In AISHELL-2, 1000 hours of clean read-speech data from iOS is published, which is free for academic usage. On top of AISHELL-2 corpus, an improved recipe is developed and released, containing key components for industrial applications, such as Chinese word segmentation, flexible vocabulary expension and phone set transformation etc. Pipelines support various state-of-the-art techniques, such as time-delayed neural networks and Lattic-Free MMI objective funciton. In addition, we also release dev and test data from other channels (Android and Mic).
(From AISHELL-2: Transforming Mandarin ASR Research Into Industrial Scale)
./RESULTS.md contains the latest results.
Transducers
There are various folders containing the name transducer in this folder.
The following table lists the differences among them.
| Encoder | Decoder | Comment | |
|---|---|---|---|
pruned_transducer_stateless5 |
Conformer(modified) | Embedding + Conv1d | same as pruned_transducer_stateless5 in librispeech recipe |
The decoder in transducer_stateless is modified from the paper
Rnn-Transducer with Stateless Prediction Network.
We place an additional Conv1d layer right after the input embedding layer.