sherpa_onnx

package module
v1.10.34 Latest Latest
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 Go to latest Published: Dec 11, 2024 License: Apache-2.0 Imports: 2 Imported by: 2

README

Introduction

This repo contains the Go package of sherpa-onnx for Linux.

Documentation

Overview

Speech recognition with Next-gen Kaldi.

sherpa-onnx is an open-source speech recognition framework for Next-gen Kaldi. It depends only on onnxruntime, supporting both streaming and non-streaming speech recognition.

It does not need to access the network during recognition and everything runs locally.

It supports a variety of platforms, such as Linux (x86_64, aarch64, arm), Windows (x86_64, x86), macOS (x86_64, arm64), etc.

Usage examples:

  1. Real-time speech recognition from a microphone

    Please see https://github.com/k2-fsa/sherpa-onnx/tree/master/go-api-examples/real-time-speech-recognition-from-microphone

  2. Decode files using a non-streaming model

    Please see https://github.com/k2-fsa/sherpa-onnx/tree/master/go-api-examples/non-streaming-decode-files

  3. Decode files using a streaming model

    Please see https://github.com/k2-fsa/sherpa-onnx/tree/master/go-api-examples/streaming-decode-files

  4. Convert text to speech using a non-streaming model

    Please see https://github.com/k2-fsa/sherpa-onnx/tree/master/go-api-examples/non-streaming-tts

Index

Constants

This section is empty.

Variables

This section is empty.

Functions

func DeleteCircularBuffer added in v1.9.15 

func DeleteCircularBuffer(buffer *CircularBuffer)

func DeleteOfflinePunc added in v1.10.29 

func DeleteOfflinePunc(punc *OfflinePunctuation)

func DeleteOfflineRecognizer 

func DeleteOfflineRecognizer(recognizer *OfflineRecognizer)

Frees the internal pointer of the recognition to avoid memory leak.

func DeleteOfflineSpeakerDiarization added in v1.10.28 

func DeleteOfflineSpeakerDiarization(sd *OfflineSpeakerDiarization)

func DeleteOfflineStream 

func DeleteOfflineStream(stream *OfflineStream)

Frees the internal pointer of the stream to avoid memory leak.

func DeleteOfflineTts added in v1.8.4 

func DeleteOfflineTts(tts *OfflineTts)

Free the internal pointer inside the tts to avoid memory leak.

func DeleteOnlineRecognizer 

func DeleteOnlineRecognizer(recognizer *OnlineRecognizer)

Free the internal pointer inside the recognizer to avoid memory leak.

func DeleteOnlineStream 

func DeleteOnlineStream(stream *OnlineStream)

Delete the internal pointer inside the stream to avoid memory leak.

func DeleteSpeakerEmbeddingExtractor added in v1.9.15 

func DeleteSpeakerEmbeddingExtractor(ex *SpeakerEmbeddingExtractor)

func DeleteSpeakerEmbeddingManager added in v1.9.15 

func DeleteSpeakerEmbeddingManager(m *SpeakerEmbeddingManager)

func DeleteSpokenLanguageIdentification added in v1.9.15 

func DeleteSpokenLanguageIdentification(slid *SpokenLanguageIdentification)

func DeleteVoiceActivityDetector added in v1.9.15 

func DeleteVoiceActivityDetector(vad *VoiceActivityDetector)

Types

type CircularBuffer added in v1.9.15 

type CircularBuffer struct {
	// contains filtered or unexported fields
}

func NewCircularBuffer added in v1.9.15 

func NewCircularBuffer(capacity int) *CircularBuffer

func (*CircularBuffer) Get added in v1.9.15 

func (buffer *CircularBuffer) Get(start int, n int) []float32

func (*CircularBuffer) Head added in v1.9.15 

func (buffer *CircularBuffer) Head() int

func (*CircularBuffer) Pop added in v1.9.15 

func (buffer *CircularBuffer) Pop(n int)

func (*CircularBuffer) Push added in v1.9.15 

func (buffer *CircularBuffer) Push(samples []float32)

func (*CircularBuffer) Reset added in v1.9.15 

func (buffer *CircularBuffer) Reset()

func (*CircularBuffer) Size added in v1.9.15 

func (buffer *CircularBuffer) Size() int

type FastClusteringConfig added in v1.10.28 

type FastClusteringConfig struct {
	NumClusters int
	Threshold   float32
}

type FeatureConfig 

type FeatureConfig struct {
	// Sample rate expected by the model. It is 16000 for all
	// pre-trained models provided by us
	SampleRate int
	// Feature dimension expected by the model. It is 80 for all
	// pre-trained models provided by us
	FeatureDim int
}

Configuration for the feature extractor

type GeneratedAudio added in v1.8.4 

type GeneratedAudio struct {
	// Normalized samples in the range [-1, 1]
	Samples []float32

	SampleRate int
}

func (*GeneratedAudio) Save added in v1.8.4 

func (audio *GeneratedAudio) Save(filename string) bool

type OfflineLMConfig 

type OfflineLMConfig struct {
	Model string  // Path to the model
	Scale float32 // scale for LM score
}

Configuration for offline LM.

type OfflineModelConfig 

type OfflineModelConfig struct {
	Transducer OfflineTransducerModelConfig
	Paraformer OfflineParaformerModelConfig
	NemoCTC    OfflineNemoEncDecCtcModelConfig
	Whisper    OfflineWhisperModelConfig
	Tdnn       OfflineTdnnModelConfig
	SenseVoice OfflineSenseVoiceModelConfig
	Moonshine  OfflineMoonshineModelConfig
	Tokens     string // Path to tokens.txt

	// Number of threads to use for neural network computation
	NumThreads int

	// 1 to print model meta information while loading
	Debug int

	// Optional. Valid values: cpu, cuda, coreml
	Provider string

	// Optional. Specify it for faster model initialization.
	ModelType string

	ModelingUnit  string // Optional. cjkchar, bpe, cjkchar+bpe
	BpeVocab      string // Optional.
	TeleSpeechCtc string // Optional.
}

type OfflineMoonshineModelConfig added in v1.10.30 

type OfflineMoonshineModelConfig struct {
	Preprocessor    string
	Encoder         string
	UncachedDecoder string
	CachedDecoder   string
}

type OfflineNemoEncDecCtcModelConfig 

type OfflineNemoEncDecCtcModelConfig struct {
	Model string // Path to the model, e.g., model.onnx or model.int8.onnx
}

Configuration for offline/non-streaming NeMo CTC models.

Please refer to https://k2-fsa.github.io/sherpa/onnx/pretrained_models/offline-ctc/index.html to download pre-trained models

type OfflineParaformerModelConfig 

type OfflineParaformerModelConfig struct {
	Model string // Path to the model, e.g., model.onnx or model.int8.onnx
}

Configuration for offline/non-streaming paraformer.

please refer to https://k2-fsa.github.io/sherpa/onnx/pretrained_models/offline-paraformer/index.html to download pre-trained models

type OfflinePunctuation added in v1.10.29 

type OfflinePunctuation struct {
	// contains filtered or unexported fields
}

func NewOfflinePunctuation added in v1.10.29 

func NewOfflinePunctuation(config *OfflinePunctuationConfig) *OfflinePunctuation

func (*OfflinePunctuation) AddPunct added in v1.10.29 

func (punc *OfflinePunctuation) AddPunct(text string) string

type OfflinePunctuationConfig added in v1.10.29 

type OfflinePunctuationConfig struct {
	Model OfflinePunctuationModelConfig
}

type OfflinePunctuationModelConfig added in v1.10.29 

type OfflinePunctuationModelConfig struct {
	CtTransformer string
	NumThreads    C.int
	Debug         C.int // true to print debug information of the model
	Provider      string
}

============================================================ For punctuation ============================================================

type OfflineRecognizer 

type OfflineRecognizer struct {
	// contains filtered or unexported fields
}

It wraps a pointer from C

func NewOfflineRecognizer 

func NewOfflineRecognizer(config *OfflineRecognizerConfig) *OfflineRecognizer

The user is responsible to invoke DeleteOfflineRecognizer() to free the returned recognizer to avoid memory leak

func (*OfflineRecognizer) Decode 

func (recognizer *OfflineRecognizer) Decode(s *OfflineStream)

Decode the offline stream.

func (*OfflineRecognizer) DecodeStreams 

func (recognizer *OfflineRecognizer) DecodeStreams(s []*OfflineStream)

Decode multiple streams in parallel, i.e., in batch.

type OfflineRecognizerConfig 

type OfflineRecognizerConfig struct {
	FeatConfig  FeatureConfig
	ModelConfig OfflineModelConfig
	LmConfig    OfflineLMConfig

	// Valid decoding method: greedy_search, modified_beam_search
	DecodingMethod string

	// Used only when DecodingMethod is modified_beam_search.
	MaxActivePaths int
	HotwordsFile   string
	HotwordsScore  float32
	BlankPenalty   float32
	RuleFsts       string
	RuleFars       string
}

Configuration for the offline/non-streaming recognizer.

type OfflineRecognizerResult 

type OfflineRecognizerResult struct {
	Text       string
	Tokens     []string
	Timestamps []float32
	Lang       string
	Emotion    string
	Event      string
}

It contains recognition result of an offline stream.

type OfflineSenseVoiceModelConfig added in v1.10.17 

type OfflineSenseVoiceModelConfig struct {
	Model                       string
	Language                    string
	UseInverseTextNormalization int
}

type OfflineSpeakerDiarization added in v1.10.28 

type OfflineSpeakerDiarization struct {
	// contains filtered or unexported fields
}

func NewOfflineSpeakerDiarization added in v1.10.28 

func NewOfflineSpeakerDiarization(config *OfflineSpeakerDiarizationConfig) *OfflineSpeakerDiarization

func (*OfflineSpeakerDiarization) Process added in v1.10.28 

func (sd *OfflineSpeakerDiarization) Process(samples []float32) []OfflineSpeakerDiarizationSegment

func (*OfflineSpeakerDiarization) SampleRate added in v1.10.28 

func (sd *OfflineSpeakerDiarization) SampleRate() int

func (*OfflineSpeakerDiarization) SetConfig added in v1.10.28 

func (sd *OfflineSpeakerDiarization) SetConfig(config *OfflineSpeakerDiarizationConfig)

only config.Clustering is used. All other fields are ignored

type OfflineSpeakerDiarizationConfig added in v1.10.28 

type OfflineSpeakerDiarizationConfig struct {
	Segmentation   OfflineSpeakerSegmentationModelConfig
	Embedding      SpeakerEmbeddingExtractorConfig
	Clustering     FastClusteringConfig
	MinDurationOn  float32
	MinDurationOff float32
}

type OfflineSpeakerDiarizationSegment added in v1.10.28 

type OfflineSpeakerDiarizationSegment struct {
	Start   float32
	End     float32
	Speaker int
}

type OfflineSpeakerSegmentationModelConfig added in v1.10.28 

type OfflineSpeakerSegmentationModelConfig struct {
	Pyannote   OfflineSpeakerSegmentationPyannoteModelConfig
	NumThreads int
	Debug      int
	Provider   string
}

type OfflineSpeakerSegmentationPyannoteModelConfig added in v1.10.28 

type OfflineSpeakerSegmentationPyannoteModelConfig struct {
	Model string
}

============================================================ For offline speaker diarization ============================================================

type OfflineStream 

type OfflineStream struct {
	// contains filtered or unexported fields
}

It wraps a pointer from C

func NewOfflineStream 

func NewOfflineStream(recognizer *OfflineRecognizer) *OfflineStream

The user is responsible to invoke DeleteOfflineStream() to free the returned stream to avoid memory leak

func (*OfflineStream) AcceptWaveform 

func (s *OfflineStream) AcceptWaveform(sampleRate int, samples []float32)

Input audio samples for the offline stream. Please only call it once. That is, input all samples at once.

sampleRate is the sample rate of the input audio samples. If it is different from the value expected by the feature extractor, we will do resampling inside.

samples contains the actual audio samples. Each sample is in the range [-1, 1].

func (*OfflineStream) GetResult 

func (s *OfflineStream) GetResult() *OfflineRecognizerResult

Get the recognition result of the offline stream.

type OfflineTdnnModelConfig added in v1.7.8 

type OfflineTdnnModelConfig struct {
	Model string
}

type OfflineTransducerModelConfig 

type OfflineTransducerModelConfig struct {
	Encoder string // Path to the encoder model, i.e., encoder.onnx or encoder.int8.onnx
	Decoder string // Path to the decoder model
	Joiner  string // Path to the joiner model
}

Configuration for offline/non-streaming transducer.

Please refer to https://k2-fsa.github.io/sherpa/onnx/pretrained_models/offline-transducer/index.html to download pre-trained models

type OfflineTts added in v1.8.4 

type OfflineTts struct {
	// contains filtered or unexported fields
}

The offline tts class. It wraps a pointer from C.

func NewOfflineTts added in v1.8.4 

func NewOfflineTts(config *OfflineTtsConfig) *OfflineTts

The user is responsible to invoke DeleteOfflineTts() to free the returned tts to avoid memory leak

func (*OfflineTts) Generate added in v1.8.4 

func (tts *OfflineTts) Generate(text string, sid int, speed float32) *GeneratedAudio

type OfflineTtsConfig added in v1.8.4 

type OfflineTtsConfig struct {
	Model           OfflineTtsModelConfig
	RuleFsts        string
	RuleFars        string
	MaxNumSentences int
}

type OfflineTtsModelConfig added in v1.8.4 

type OfflineTtsModelConfig struct {
	Vits OfflineTtsVitsModelConfig

	// Number of threads to use for neural network computation
	NumThreads int

	// 1 to print model meta information while loading
	Debug int

	// Optional. Valid values: cpu, cuda, coreml
	Provider string
}

type OfflineTtsVitsModelConfig added in v1.8.4 

type OfflineTtsVitsModelConfig struct {
	Model       string  // Path to the VITS onnx model
	Lexicon     string  // Path to lexicon.txt
	Tokens      string  // Path to tokens.txt
	DataDir     string  // Path to espeak-ng-data directory
	NoiseScale  float32 // noise scale for vits models. Please use 0.667 in general
	NoiseScaleW float32 // noise scale for vits models. Please use 0.8 in general
	LengthScale float32 // Please use 1.0 in general. Smaller -> Faster speech speed. Larger -> Slower speech speed
	DictDir     string  // Path to dict directory for jieba (used only in Chinese tts)
}

Configuration for offline/non-streaming text-to-speech (TTS).

Please refer to https://k2-fsa.github.io/sherpa/onnx/tts/pretrained_models/index.html to download pre-trained models

type OfflineWhisperModelConfig added in v1.7.8 

type OfflineWhisperModelConfig struct {
	Encoder      string
	Decoder      string
	Language     string
	Task         string
	TailPaddings int
}

type OnlineCtcFstDecoderConfig added in v1.9.16 

type OnlineCtcFstDecoderConfig struct {
	Graph     string
	MaxActive int
}

type OnlineModelConfig added in v1.7.6 

type OnlineModelConfig struct {
	Transducer    OnlineTransducerModelConfig
	Paraformer    OnlineParaformerModelConfig
	Zipformer2Ctc OnlineZipformer2CtcModelConfig
	Tokens        string // Path to tokens.txt
	NumThreads    int    // Number of threads to use for neural network computation
	Provider      string // Optional. Valid values are: cpu, cuda, coreml
	Debug         int    // 1 to show model meta information while loading it.
	ModelType     string // Optional. You can specify it for faster model initialization
	ModelingUnit  string // Optional. cjkchar, bpe, cjkchar+bpe
	BpeVocab      string // Optional.
	TokensBuf     string // Optional.
	TokensBufSize int    // Optional.
}

Configuration for online/streaming models

Please refer to https://k2-fsa.github.io/sherpa/onnx/pretrained_models/online-transducer/index.html https://k2-fsa.github.io/sherpa/onnx/pretrained_models/online-paraformer/index.html to download pre-trained models

type OnlineParaformerModelConfig added in v1.7.6 

type OnlineParaformerModelConfig struct {
	Encoder string // Path to the encoder model, e.g., encoder.onnx or encoder.int8.onnx
	Decoder string // Path to the decoder model.
}

Configuration for online/streaming paraformer models

Please refer to https://k2-fsa.github.io/sherpa/onnx/pretrained_models/online-paraformer/index.html to download pre-trained models

type OnlineRecognizer 

type OnlineRecognizer struct {
	// contains filtered or unexported fields
}

The online recognizer class. It wraps a pointer from C.

func NewOnlineRecognizer 

func NewOnlineRecognizer(config *OnlineRecognizerConfig) *OnlineRecognizer

The user is responsible to invoke DeleteOnlineRecognizer() to free the returned recognizer to avoid memory leak

func (*OnlineRecognizer) Decode 

func (recognizer *OnlineRecognizer) Decode(s *OnlineStream)

Decode the stream. Before calling this function, you have to ensure that recognizer.IsReady(s) returns true. Otherwise, you will be SAD.

You usually use it like below: 

for recognizer.IsReady(s) {
  recognizer.Decode(s)
}

func (*OnlineRecognizer) DecodeStreams 

func (recognizer *OnlineRecognizer) DecodeStreams(s []*OnlineStream)

Decode multiple streams in parallel, i.e., in batch. You have to ensure that each stream is ready for decoding. Otherwise, you will be SAD.

func (*OnlineRecognizer) GetResult 

func (recognizer *OnlineRecognizer) GetResult(s *OnlineStream) *OnlineRecognizerResult

Get the current result of stream since the last invoke of Reset()

func (*OnlineRecognizer) IsEndpoint 

func (recognizer *OnlineRecognizer) IsEndpoint(s *OnlineStream) bool

Return true if an endpoint is detected.

You usually use it like below: 

if recognizer.IsEndpoint(s) {
   // do your own stuff after detecting an endpoint

   recognizer.Reset(s)
}

func (*OnlineRecognizer) IsReady 

func (recognizer *OnlineRecognizer) IsReady(s *OnlineStream) bool

Check whether the stream has enough feature frames for decoding. Return true if this stream is ready for decoding. Return false otherwise.

You will usually use it like below: 

for recognizer.IsReady(s) {
   recognizer.Decode(s)
}

func (*OnlineRecognizer) Reset 

func (recognizer *OnlineRecognizer) Reset(s *OnlineStream)

After calling this function, the internal neural network model states are reset and IsEndpoint(s) would return false. GetResult(s) would also return an empty string.

type OnlineRecognizerConfig 

type OnlineRecognizerConfig struct {
	FeatConfig  FeatureConfig
	ModelConfig OnlineModelConfig

	// Valid decoding methods: greedy_search, modified_beam_search
	DecodingMethod string

	// Used only when DecodingMethod is modified_beam_search. It specifies
	// the maximum number of paths to keep during the search
	MaxActivePaths int

	EnableEndpoint int // 1 to enable endpoint detection.

	// Please see
	// https://k2-fsa.github.io/sherpa/ncnn/endpoint.html
	// for the meaning of Rule1MinTrailingSilence, Rule2MinTrailingSilence
	// and Rule3MinUtteranceLength.
	Rule1MinTrailingSilence float32
	Rule2MinTrailingSilence float32
	Rule3MinUtteranceLength float32
	HotwordsFile            string
	HotwordsScore           float32
	BlankPenalty            float32
	CtcFstDecoderConfig     OnlineCtcFstDecoderConfig
	RuleFsts                string
	RuleFars                string
	HotwordsBuf             string
	HotwordsBufSize         int
}

Configuration for the online/streaming recognizer.

type OnlineRecognizerResult 

type OnlineRecognizerResult struct {
	Text string
}

It contains the recognition result for a online stream.

type OnlineStream 

type OnlineStream struct {
	// contains filtered or unexported fields
}

The online stream class. It wraps a pointer from C.

func NewOnlineStream 

func NewOnlineStream(recognizer *OnlineRecognizer) *OnlineStream

The user is responsible to invoke DeleteOnlineStream() to free the returned stream to avoid memory leak

func (*OnlineStream) AcceptWaveform 

func (s *OnlineStream) AcceptWaveform(sampleRate int, samples []float32)

Input audio samples for the stream.

sampleRate is the actual sample rate of the input audio samples. If it is different from the sample rate expected by the feature extractor, we will do resampling inside.

samples contains audio samples. Each sample is in the range [-1, 1]

func (*OnlineStream) InputFinished 

func (s *OnlineStream) InputFinished()

Signal that there will be no incoming audio samples. After calling this function, you cannot call OnlineStream.AcceptWaveform any longer.

The main purpose of this function is to flush the remaining audio samples buffered inside for feature extraction.

type OnlineTransducerModelConfig 

type OnlineTransducerModelConfig struct {
	Encoder string // Path to the encoder model, e.g., encoder.onnx or encoder.int8.onnx
	Decoder string // Path to the decoder model.
	Joiner  string // Path to the joiner model.
}

Configuration for online/streaming transducer models

Please refer to https://k2-fsa.github.io/sherpa/onnx/pretrained_models/online-transducer/index.html to download pre-trained models

type OnlineZipformer2CtcModelConfig added in v1.9.7 

type OnlineZipformer2CtcModelConfig struct {
	Model string // Path to the onnx model
}

Please refer to https://k2-fsa.github.io/sherpa/onnx/pretrained_models/online-ctc/index.html to download pre-trained models

type SileroVadModelConfig added in v1.9.15 

type SileroVadModelConfig struct {
	Model              string
	Threshold          float32
	MinSilenceDuration float32
	MinSpeechDuration  float32
	WindowSize         int
	MaxSpeechDuration  float32
}

============================================================ For VAD ============================================================

type SpeakerEmbeddingExtractor added in v1.9.15 

type SpeakerEmbeddingExtractor struct {
	// contains filtered or unexported fields
}

func NewSpeakerEmbeddingExtractor added in v1.9.15 

func NewSpeakerEmbeddingExtractor(config *SpeakerEmbeddingExtractorConfig) *SpeakerEmbeddingExtractor

The user has to invoke DeleteSpeakerEmbeddingExtractor() to free the returned value to avoid memory leak

func (*SpeakerEmbeddingExtractor) Compute added in v1.9.15 

func (ex *SpeakerEmbeddingExtractor) Compute(stream *OnlineStream) []float32

func (*SpeakerEmbeddingExtractor) CreateStream added in v1.9.15 

func (ex *SpeakerEmbeddingExtractor) CreateStream() *OnlineStream

The user is responsible to invoke DeleteOnlineStream() to free the returned stream to avoid memory leak

func (*SpeakerEmbeddingExtractor) Dim added in v1.9.15 

func (ex *SpeakerEmbeddingExtractor) Dim() int

func (*SpeakerEmbeddingExtractor) IsReady added in v1.9.15 

func (ex *SpeakerEmbeddingExtractor) IsReady(stream *OnlineStream) bool

type SpeakerEmbeddingExtractorConfig added in v1.9.15 

type SpeakerEmbeddingExtractorConfig struct {
	Model      string
	NumThreads int
	Debug      int
	Provider   string
}

type SpeakerEmbeddingManager added in v1.9.15 

type SpeakerEmbeddingManager struct {
	// contains filtered or unexported fields
}

func NewSpeakerEmbeddingManager added in v1.9.15 

func NewSpeakerEmbeddingManager(dim int) *SpeakerEmbeddingManager

The user has to invoke DeleteSpeakerEmbeddingManager() to free the returned value to avoid memory leak

func (*SpeakerEmbeddingManager) AllSpeakers added in v1.9.15 

func (m *SpeakerEmbeddingManager) AllSpeakers() []string

func (*SpeakerEmbeddingManager) Contains added in v1.9.15 

func (m *SpeakerEmbeddingManager) Contains(name string) bool

func (*SpeakerEmbeddingManager) NumSpeakers added in v1.9.15 

func (m *SpeakerEmbeddingManager) NumSpeakers() int

func (*SpeakerEmbeddingManager) Register added in v1.9.15 

func (m *SpeakerEmbeddingManager) Register(name string, embedding []float32) bool

func (*SpeakerEmbeddingManager) RegisterV added in v1.9.15 

func (m *SpeakerEmbeddingManager) RegisterV(name string, embeddings [][]float32) bool

func (*SpeakerEmbeddingManager) Remove added in v1.9.15 

func (m *SpeakerEmbeddingManager) Remove(name string) bool

func (*SpeakerEmbeddingManager) Search added in v1.9.15 

func (m *SpeakerEmbeddingManager) Search(embedding []float32, threshold float32) string

func (*SpeakerEmbeddingManager) Verify added in v1.9.15 

func (m *SpeakerEmbeddingManager) Verify(name string, embedding []float32, threshold float32) bool

type SpeechSegment added in v1.9.15 

type SpeechSegment struct {
	Start   int
	Samples []float32
}

type SpokenLanguageIdentification added in v1.9.15 

type SpokenLanguageIdentification struct {
	// contains filtered or unexported fields
}

func NewSpokenLanguageIdentification added in v1.9.15 

func NewSpokenLanguageIdentification(config *SpokenLanguageIdentificationConfig) *SpokenLanguageIdentification

func (*SpokenLanguageIdentification) Compute added in v1.9.15 

func (slid *SpokenLanguageIdentification) Compute(stream *OfflineStream) *SpokenLanguageIdentificationResult

func (*SpokenLanguageIdentification) CreateStream added in v1.9.15 

func (slid *SpokenLanguageIdentification) CreateStream() *OfflineStream

The user has to invoke DeleteOfflineStream() to free the returned value to avoid memory leak

type SpokenLanguageIdentificationConfig added in v1.9.15 

type SpokenLanguageIdentificationConfig struct {
	Whisper    SpokenLanguageIdentificationWhisperConfig
	NumThreads int
	Debug      int
	Provider   string
}

type SpokenLanguageIdentificationResult added in v1.9.15 

type SpokenLanguageIdentificationResult struct {
	Lang string
}

type SpokenLanguageIdentificationWhisperConfig added in v1.9.15 

type SpokenLanguageIdentificationWhisperConfig struct {
	Encoder      string
	Decoder      string
	TailPaddings int
}

type VadModelConfig added in v1.9.15 

type VadModelConfig struct {
	SileroVad  SileroVadModelConfig
	SampleRate int
	NumThreads int
	Provider   string
	Debug      int
}

type VoiceActivityDetector added in v1.9.15 

type VoiceActivityDetector struct {
	// contains filtered or unexported fields
}

func NewVoiceActivityDetector added in v1.9.15 

func NewVoiceActivityDetector(config *VadModelConfig, bufferSizeInSeconds float32) *VoiceActivityDetector

func (*VoiceActivityDetector) AcceptWaveform added in v1.9.15 

func (vad *VoiceActivityDetector) AcceptWaveform(samples []float32)

func (*VoiceActivityDetector) Clear added in v1.9.15 

func (vad *VoiceActivityDetector) Clear()

func (*VoiceActivityDetector) Flush added in v1.10.13 

func (vad *VoiceActivityDetector) Flush()

func (*VoiceActivityDetector) Front added in v1.9.15 

func (vad *VoiceActivityDetector) Front() *SpeechSegment

func (*VoiceActivityDetector) IsEmpty added in v1.9.15 

func (vad *VoiceActivityDetector) IsEmpty() bool

func (*VoiceActivityDetector) IsSpeech added in v1.9.15 

func (vad *VoiceActivityDetector) IsSpeech() bool

func (*VoiceActivityDetector) Pop added in v1.9.15 

func (vad *VoiceActivityDetector) Pop()

func (*VoiceActivityDetector) Reset added in v1.9.15 

func (vad *VoiceActivityDetector) Reset()

type Wave added in v1.9.15 

type Wave = GeneratedAudio

single channel wave

func ReadWave added in v1.9.15 

func ReadWave(filename string) *Wave

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