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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
A No-Recurrence Sequence-to-Sequence Model for Speech Recognition
| Date | Stars |
|---|---|
| 2026-07-31 | 378 |
| 2026-08-06 | 378 |
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# OpenTransformer This is a speech-transformer model for end-to-end speech recognition. If you have any questions, please email to me. ([email protected]) # Requirements Pytorch >= 1.2.0 (<= 1.6.0) Torchaudio >= 0.3.0 ## TO DO - [ ] Reduce the redundant computation by cache the previous states during inference ## Function - Speech Transformer / Conformer - Label Smoothing - Tie Weights of Embedding with output softmax layer - Data Augmentation([SpecAugument](https://arxiv.org/abs/1904.08779)) - Extract Fbank features in a online fashion - Read the feature with the kaldi or espnet format! - Visualization based Tensorboard [Will Be Updated Soon!] - Batch Beam Search with Length Penalty - Multiple Optimizers and Schedulers - Multiple Activation Functions in FFN - Multi GPU - LM Shollow Fusion ## Prepare vocab ``` # character idx <PAD> 0 <S/E> 1 <UNK> 2 我 3 你 4 ... ``` character ``` BAC009S0764W0139 国 家 统 计 局 的 数 据 显 示 BAC009S0764W0140 其 中 广 州 深 圳 甚 至 出 现 了 多 个 日 光 盘 BAC009S0764W0141 零 三 年 到 去 年 BAC009S0764W0142 市 场 基 数 已 不 可 同 日 而 语 BAC009S0764W0143 在 市 场 整 体 从 高 速 增 长 进 入 中 高 速 增 长 区 间 的 同 时 BAC009S0764W0144 一 线 城 市 在 价 格 较 高 的 基 础 上 整 体 回 升 并 领 涨 全 国 BAC009S0764W0145 绝 大 部 分 三 线 城 市 房 价 仍 然 下 降 BAC009S0764W0146 一 线 楼 市 成 交 量 激 增 BAC009S0764W0147 三 四 线 城 市 依 然 冷 清 ``` if you want to compute features online, please make sure you have a wav.scp file. ``` # wav.scp # id path BAC009S0764W0139 /data/aishell/wav/BAC009S0764W0139.wav ``` ## Train - Single GPU ```python python run.py -c egs/aishell/conf/transformer.yaml ``` - Multi GPU Training based DataParallel ```python python run.py -c egs/aishell/transformer.yaml -n 2 -g 0,1 ``` ## Average the parameters of the last N epochs ```python python tools/average.py your_model_expdir 50 59 # average the models from 50-th epoch to 59-th epoch ``` ## Eval ```python python eval.py -m model.pt ``` ## Experiments Our Model can achieve a CER of 6.7% without CMVN, any external LM and joint-CTC training on [AISHELL-1](http://www.openslr.org/33/), which is better than 7.4% of Chain Model in Kaldi. ## Acknowledge OpenTransformer refer to [ESPNET](https://github.com/espnet/espnet).
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:6384b186c27841d8, desc:speech recognition