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update websocket_protocol

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雾聪 2024-01-08 16:49:24 +08:00
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8
runtime/docs/websocket_protocol.md
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@ -36,7 +36,7 @@ After sending the audio data, an end-of-audio flag needs to be sent (which needs
#### Sending Recognition Results #### Sending Recognition Results
The message (serialized in JSON) is: The message (serialized in JSON) is:
```text ```text
{"mode": "offline", "wav_name": "wav_name", "text": "asr ouputs", "is_final": True, "timestamp":"[[100,200], [200,500]]", "stamp_sents":""} {"mode": "offline", "wav_name": "wav_name", "text": "asr ouputs", "is_final": True, "timestamp":"[[100,200], [200,500]]", "stamp_sents":[]}
``` ```
Parameter explanation: Parameter explanation:
```text ```text
@ -45,7 +45,7 @@ Parameter explanation:
`text`: the text output of speech recognition `text`: the text output of speech recognition
`is_final`: indicating the end of recognition `is_final`: indicating the end of recognition
`timestamp`：If AM is a timestamp model, it will return this field, indicating the timestamp, in the format of "[[100,200], [200,500]]" `timestamp`：If AM is a timestamp model, it will return this field, indicating the timestamp, in the format of "[[100,200], [200,500]]"
`stamp_sents`：If AM is a timestamp model, it will return this field, indicating the stamp_sents, in the format of "[{'text_seg':'正 是 因 为','punc':',','start':'430','end':'1130','ts_list':[[430,670],[670,810],[810,1030],[1030,1130]]}]" `stamp_sents`：If AM is a timestamp model, it will return this field, indicating the stamp_sents, in the format of [{"text_seg":"正 是 因 为","punc":",","start":"430","end":"1130","ts_list":[[430,670],[670,810],[810,1030],[1030,1130]]}]
``` ```
## Real-time Speech Recognition ## Real-time Speech Recognition
@ -85,7 +85,7 @@ After sending the audio data, an end-of-audio flag needs to be sent (which needs
The message (serialized in JSON) is: The message (serialized in JSON) is:
```text ```text
{"mode": "2pass-online", "wav_name": "wav_name", "text": "asr ouputs", "is_final": True, "timestamp":"[[100,200], [200,500]]", "stamp_sents":""} {"mode": "2pass-online", "wav_name": "wav_name", "text": "asr ouputs", "is_final": True, "timestamp":"[[100,200], [200,500]]", "stamp_sents":[]}
``` ```
Parameter explanation: Parameter explanation:
```text ```text
@ -94,5 +94,5 @@ Parameter explanation:
`text`: the text output of speech recognition `text`: the text output of speech recognition
`is_final`: indicating the end of recognition `is_final`: indicating the end of recognition
`timestamp`：If AM is a timestamp model, it will return this field, indicating the timestamp, in the format of "[[100,200], [200,500]]" `timestamp`：If AM is a timestamp model, it will return this field, indicating the timestamp, in the format of "[[100,200], [200,500]]"
`stamp_sents`：If AM is a timestamp model, it will return this field, indicating the stamp_sents, in the format of "[{'text_seg':'正 是 因 为','punc':',','start':'430','end':'1130','ts_list':[[430,670],[670,810],[810,1030],[1030,1130]]}]" `stamp_sents`：If AM is a timestamp model, it will return this field, indicating the stamp_sents, in the format of [{"text_seg":"正 是 因 为","punc":",","start":"430","end":"1130","ts_list":[[430,670],[670,810],[810,1030],[1030,1130]]}]
``` ```

8
runtime/docs/websocket_protocol_zh.md
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@ -37,7 +37,7 @@ pcm直接将音频数据，其他格式音频数据，连同头部信息与音
#### 发送识别结果 #### 发送识别结果
message为（采用json序列化） message为（采用json序列化）
```text ```text
{"mode": "offline", "wav_name": "wav_name", "text": "asr ouputs", "is_final": True,"timestamp":"[[100,200], [200,500]]","stamp_sents":""} {"mode": "offline", "wav_name": "wav_name", "text": "asr ouputs", "is_final": True,"timestamp":"[[100,200], [200,500]]","stamp_sents":[]}
``` ```
参数介绍： 参数介绍：
```text ```text
@ -46,7 +46,7 @@ message为（采用json序列化）
`text`：表示语音识别输出文本 `text`：表示语音识别输出文本
`is_final`：表示识别结束 `is_final`：表示识别结束
`timestamp`：如果AM为时间戳模型，会返回此字段，表示时间戳，格式为 "[[100,200], [200,500]]"(ms) `timestamp`：如果AM为时间戳模型，会返回此字段，表示时间戳，格式为 "[[100,200], [200,500]]"(ms)
`stamp_sents`：如果AM为时间戳模型，会返回此字段，表示句子级别时间戳，格式为 "[{'text_seg':'正 是 因 为','punc':',','start':'430','end':'1130','ts_list':[[430,670],[670,810],[810,1030],[1030,1130]]}]" `stamp_sents`：如果AM为时间戳模型，会返回此字段，表示句子级别时间戳，格式为 [{"text_seg":"正 是 因 为","punc":",","start":"430","end":"1130","ts_list":[[430,670],[670,810],[810,1030],[1030,1130]]}]
``` ```
## 实时语音识别 ## 实时语音识别
@ -87,7 +87,7 @@ message为（需要用json序列化）：
#### 发送识别结果 #### 发送识别结果
message为（采用json序列化） message为（采用json序列化）
```text ```text
{"mode": "2pass-online", "wav_name": "wav_name", "text": "asr ouputs", "is_final": True, "timestamp":"[[100,200], [200,500]]","stamp_sents":""} {"mode": "2pass-online", "wav_name": "wav_name", "text": "asr ouputs", "is_final": True, "timestamp":"[[100,200], [200,500]]","stamp_sents":[]}
``` ```
参数介绍： 参数介绍：
```text ```text
@ -96,5 +96,5 @@ message为（采用json序列化）
`text`：表示语音识别输出文本 `text`：表示语音识别输出文本
`is_final`：表示识别结束 `is_final`：表示识别结束
`timestamp`：如果AM为时间戳模型，会返回此字段，表示时间戳，格式为 "[[100,200], [200,500]]"(ms) `timestamp`：如果AM为时间戳模型，会返回此字段，表示时间戳，格式为 "[[100,200], [200,500]]"(ms)
`stamp_sents`：如果AM为时间戳模型，会返回此字段，表示句子级别时间戳，格式为 "[{'text_seg':'正 是 因 为','punc':',','start':'430','end':'1130','ts_list':[[430,670],[670,810],[810,1030],[1030,1130]]}]" `stamp_sents`：如果AM为时间戳模型，会返回此字段，表示句子级别时间戳，格式为 [{"text_seg":"正 是 因 为","punc":",","start":"430","end":"1130","ts_list":[[430,670],[670,810],[810,1030],[1030,1130]]}]
``` ```