| | |
|---|
| | | self.client_buffers = {} |
|---|
| | | self.client_transcription = {} |
|---|
| | | self.auth_user = user_allowed.split("|") |
|---|
| | | self.inference_16k_pipline = pipeline(task=Tasks.auto_speech_recognition, model=model) |
|---|
| | | self.inference_16k_pipeline = pipeline(task=Tasks.auto_speech_recognition, model=model) |
|---|
| | | self.sample_rate = sample_rate |
|---|
| | | |
|---|
| | | def clear_states(self, user): |
|---|
| | |
|---|
| | | result["detail"] = "decoding data: %d bytes" % len(tmp_data) |
|---|
| | | result["text"] = "" |
|---|
| | | yield Response(sentence=json.dumps(result), user=req.user, action="decoding", language=req.language) |
|---|
| | | if len(tmp_data) < 800: #min input_len for asr model |
|---|
| | | if len(tmp_data) < 9600: #min input_len for asr model , 300ms |
|---|
| | | end_time = int(round(time.time() * 1000)) |
|---|
| | | delay_str = str(end_time - begin_time) |
|---|
| | | result = {} |
|---|
| | |
|---|
| | | print ("user: %s , delay(ms): %s, error: %s " % (req.user, delay_str, "data_is_not_long_enough")) |
|---|
| | | yield Response(sentence=json.dumps(result), user=req.user, action="finish", language=req.language) |
|---|
| | | else: |
|---|
| | | asr_result = self.inference_16k_pipline(audio_in=tmp_data, audio_fs = self.sample_rate) |
|---|
| | | asr_result = self.inference_16k_pipeline(audio_in=tmp_data, audio_fs = self.sample_rate) |
|---|
| | | if "text" in asr_result: |
|---|
| | | asr_result = asr_result['text'] |
|---|
| | | else: |
|---|
