Paraformer real-time speech recognition Android SDK

Invocation steps

1. Initialize the SDK.

2. Set the required parameters. Use the parameters parameter of the initialize method to set connection and control parameters. Use the setParams method to set speech recognition effect parameters.

3. Call startDialog to start the recognition process.

4. In the onNuiAudioStateChanged callback, start the recording device based on the audio state.

5. In the onNuiNeedAudioData callback, continuously provide recording data.

6. In the onNuiEventCallback callback, listen for events and retrieve the speech recognition results.

7. Call stopDialog to stop recognition. Confirm that recognition has ended by listening for the EVENT_TRANSCRIBER_COMPLETE event.

8. When the recognition feature is no longer needed, call the release method to release SDK resources.

Connection and control parameters

You can configure these parameters by passing a JSON string in the parameters parameter of the initialize method.

• Parameter example: The following code provides a sample JSON string. Not all parameters are listed. You can add parameters as needed during encoding:

  {
      "url": "wss://dashscope.aliyuncs.com/api-ws/v1/inference",
      "apikey": "st-****",
      "device_id": "my_device_id",
      "service_mode": "1"
  }

• Parameter descriptions

  Parameter	Type	Required	Description
  url	String	Yes	The service endpoint. This is fixed at wss://dashscope.aliyuncs.com/api-ws/v1/inference.
  apikey	String	Yes	The API key. To reduce the risk of a long-term key being exposed, use a more secure temporary API key with a short validity period.
  service_mode	String	Yes	The operating mode. For real-time speech recognition, this is fixed at "1".
  device_id	String	Yes	A unique string that identifies the end user. You can set this to an in-app user ID or a unique device identifier generated by the client. This ID is mainly used for log tracking and troubleshooting.
  debug_path	String	No	The storage path for log files. This parameter takes effect only when save_log is set to true in the initialize call. You must set a log file path, otherwise an error will occur. A maximum of two log files are kept locally.
  save_wav	String	No	Specifies whether to save audio files for debugging. The audio files are saved to the path specified by debug_path. Default value: "false". Valid values: "true": Yes "false": No This parameter takes effect only when save_log is set to true in the initialize call. The debug_path parameter must also be set.
  max_log_file_size	int	No	The maximum size of a log file in bytes. This parameter takes effect only when save_log is set to true in the initialize call. Default value: 104857600 (100 × 1024 × 1024 bytes, which is 100 MiB).
  log_track_level	int	No	Controls the filter level of log content sent externally through the log callback (<a baseurl="t3166292_v1_0_0.xdita" data-node="6183301" data-root="85177" data-tag="xref" href="#9c10968457gc6" id="0002fe9689yts">onNuiLogTrackCallback</a>). Default value: 2. Valid values: 0: LOG_LEVEL_VERBOSE 1: LOG_LEVEL_DEBUG 2: LOG_LEVEL_INFO 3: LOG_LEVEL_WARNING 4: LOG_LEVEL_ERROR 5: LOG_LEVEL_NONE (disables this feature) Note: log_track_level and level (set through the initialize interface) together determine the final logs that are sent to the callback. A log is sent to the callback only if its level value is greater than or equal to both the log_track_level and level values. For example, if log_track_level is set to 2 (INFO) and level is set to 3 (WARNING), only logs at the WARNING level and higher (value >= 3) are sent to the callback.

Speech recognition effect parameters

You can configure these parameters by passing a JSON string in the params parameter of the setParams method.

• Parameter example: The following code provides a sample JSON string. Not all parameters are listed. You can add parameters as needed during encoding:

  {
      "service_type": 4,
      "nls_config": {
          "model": "paraformer-realtime-v2",
          "sr_format": "pcm",
          "sample_rate": "16000"
      }
  }

• Parameter descriptions

  Top-level parameter	Type	Required	Description
  service_type	int	Yes	The Voice Service type. For real-time speech recognition, this is fixed at 4.
  nls_config	object	Yes	The core configuration object for speech recognition. It contains key parameters such as model selection and recognition effect controls.
  nls_config.model	string	Yes	The speech recognition model.
  nls_config.sr_format	string	Yes	The format of the audio to be recognized. Supported audio formats: pcm, wav, opus. Important opus: Must be PCM encoded. The SDK internally encodes it into the OPUS format. wav/pcm: Must be PCM encoded.
  nls_config.sample_rate	int	Yes	The sample rate of the audio to be recognized, in Hz. This varies by model: paraformer-realtime-v2 supports any sample rate. paraformer-realtime-v1 only supports a 16000 Hz sample rate. paraformer-realtime-8k-v2 only supports an 8000 Hz sample rate. paraformer-realtime-8k-v1 only supports an 8000 Hz sample rate.
  nls_config.disfluency_removal_enabled	boolean	No	Specifies whether to filter out filler words, such as "um" and "ah". Default value: false.
  nls_config.language_hints	array[string]	No	Sets the language codes for recognition. If you cannot determine the language in advance, you can leave this unset. The model will automatically detect the language. Supported language codes: zh: Chinese en: English ja: Japanese yue: Cantonese ko: Korean de: German fr: French ru: Russian This parameter only takes effect for multilingual models.
  nls_config.semantic_punctuation_enabled	boolean	No	Sets the sentence segmentation mode. Default value: false. Valid values: true: Enables semantic segmentation and disables VAD segmentation. false: Enables VAD segmentation and disables semantic segmentation. Semantic segmentation provides higher accuracy and is suitable for meeting transcription scenarios. Voice Activity Detection (VAD) segmentation has lower latency and is suitable for real-time interactive scenarios. This parameter takes effect only for v2 and later models.
  nls_config.max_sentence_silence	int	No	The silence duration threshold for VAD segmentation, in ms. Default value: 800. Value range: [200, 6000]. When the silence duration after a speech segment exceeds this threshold, the system determines that the sentence has ended. This parameter takes effect only when the semantic_punctuation_enabled parameter is false and for v2 and later models.
  nls_config.multi_threshold_mode_enabled	boolean	No	Specifies whether to enable the long-segment prevention mode. Enabling this prevents VAD from creating excessively long segments. Default value: false (disabled). Valid values: true: Enabled false: Disabled This parameter takes effect only when the semantic_punctuation_enabled parameter is false and for v2 and later models.
  nls_config.punctuation_prediction_enabled	boolean	No	Specifies whether to automatically add punctuation to the recognition results. Default value: true (yes). Valid values: true: Yes false: No This parameter takes effect only for v2 and later models.
  nls_config.heartbeat	boolean	No	Specifies whether to maintain a persistent connection with the server. Default value: false. Valid values: true: The connection to the server can be maintained without interruption by continuously sending silent audio. false: The connection will be disconnected due to a timeout after 60 seconds, even if silent audio is continuously sent. This 60-second timeout is a default server-side behavior and cannot be configured by the client. This parameter takes effect only for v2 and later models.
  nls_config.inverse_text_normalization_enabled	boolean	No	Specifies whether to enable Inverse Text Normalization (ITN). When enabled, Chinese numerals are converted to Arabic numerals. Default value: true (enabled). Valid values: true: Enabled false: Disabled This parameter takes effect only for v2 and later models.
  nls_config.vocabulary_id	string	No	The ID of the hotword vocabulary, used to improve the recognition accuracy of specific words. This parameter applies to v2 and later models. For information about how to use hotwords, see Customize hotwords.
  nls_config.resources	array[object]	No	The hotword resource configuration for v1 models. This feature is the same as vocabulary_id but is configured differently: resources is an array of objects. Each element contains the resource_id and resource_type fields: resource_id: A string that specifies the hotword ID. resource_type: A string with a fixed value of "asr_phrase". Example: { "nls_config": { "resources": [ { "resource_id": "xxxxxxxxxxxx", "resource_type": "asr_phrase" } ] } } For information about how to use hotwords, see Customize and manage Paraformer speech recognition hotwords.

NativeNui

INativeNuiCallback: Listener callbacks

default void onNuiLogTrackCallback(Constants.LogLevel level, String log)

NuiEvent: Event types