streaming bugfix (#1271)
* funasr1.0 funetine
* funasr1.0 pbar
* update with main (#1260)
* Update websocket_protocol_zh.md
* update
---------
Co-authored-by: Yabin Li <wucong.lyb@alibaba-inc.com>
Co-authored-by: shixian.shi <shixian.shi@alibaba-inc.com>
* update with main (#1264)
* Funasr1.0 (#1261)
* funasr1.0 funetine
* funasr1.0 pbar
* update with main (#1260)
* Update websocket_protocol_zh.md
* update
---------
Co-authored-by: Yabin Li <wucong.lyb@alibaba-inc.com>
Co-authored-by: shixian.shi <shixian.shi@alibaba-inc.com>
---------
Co-authored-by: Yabin Li <wucong.lyb@alibaba-inc.com>
Co-authored-by: shixian.shi <shixian.shi@alibaba-inc.com>
* bug fix
---------
Co-authored-by: Yabin Li <wucong.lyb@alibaba-inc.com>
Co-authored-by: shixian.shi <shixian.shi@alibaba-inc.com>
* funasr1.0 sanm scama
* funasr1.0 infer_after_finetune
* funasr1.0 fsmn-vad bug fix
* funasr1.0 fsmn-vad bug fix
* funasr1.0 fsmn-vad bug fix
---------
Co-authored-by: Yabin Li <wucong.lyb@alibaba-inc.com>
Co-authored-by: shixian.shi <shixian.shi@alibaba-inc.com>
| | |
| | | decoder_chunk_look_back = 1 #number of encoder chunks to lookback for decoder cross-attention |
| | | |
| | | model = AutoModel(model="damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-online", model_revision="v2.0.2") |
| | | cache = {} |
| | | res = model.generate(input="https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav", |
| | | chunk_size=chunk_size, |
| | | encoder_chunk_look_back=encoder_chunk_look_back, |
| | |
| | | # self.AllResetDetection() |
| | | return segments |
| | | |
| | | |
| | | def init_cache(self, cache: dict = {}, **kwargs): |
| | | |
| | | cache["frontend"] = {} |
| | | cache["prev_samples"] = torch.empty(0) |
| | | cache["encoder"] = {} |
| | |
| | | |
| | | cache["prev_samples"] = audio_sample[:-m] |
| | | if _is_final: |
| | | cache = {} |
| | | self.init_cache(cache) |
| | | |
| | | ibest_writer = None |
| | | if ibest_writer is None and kwargs.get("output_dir") is not None: |
| | |
| | | self.init_beam_search(**kwargs) |
| | | self.nbest = kwargs.get("nbest", 1) |
| | | |
| | | |
| | | if len(cache) == 0: |
| | | self.init_cache(cache, **kwargs) |
| | | |