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enginex-mr_series-sherpa-onnx/ios-swift/SherpaOnnx/SherpaOnnx/ViewController.swift
2024-03-28 18:05:40 +08:00

203 lines
6.1 KiB
Swift

//
// ViewController.swift
// SherpaOnnx
//
// Created by fangjun on 2023/1/28.
//
import AVFoundation
import UIKit
extension AudioBuffer {
func array() -> [Float] {
return Array(UnsafeBufferPointer(self))
}
}
extension AVAudioPCMBuffer {
func array() -> [Float] {
return self.audioBufferList.pointee.mBuffers.array()
}
}
class ViewController: UIViewController {
@IBOutlet weak var resultLabel: UILabel!
@IBOutlet weak var recordBtn: UIButton!
var audioEngine: AVAudioEngine? = nil
var recognizer: SherpaOnnxRecognizer! = nil
/// It saves the decoded results so far
var sentences: [String] = [] {
didSet {
updateLabel()
}
}
var lastSentence: String = ""
let maxSentence: Int = 20
var results: String {
if sentences.isEmpty && lastSentence.isEmpty {
return ""
}
if sentences.isEmpty {
return "0: \(lastSentence.lowercased())"
}
let start = max(sentences.count - maxSentence, 0)
if lastSentence.isEmpty {
return sentences.enumerated().map { (index, s) in "\(index): \(s.lowercased())" }[start...]
.joined(separator: "\n")
} else {
return sentences.enumerated().map { (index, s) in "\(index): \(s.lowercased())" }[start...]
.joined(separator: "\n") + "\n\(sentences.count): \(lastSentence.lowercased())"
}
}
func updateLabel() {
DispatchQueue.main.async {
self.resultLabel.text = self.results
}
}
override func viewDidLoad() {
super.viewDidLoad()
// Do any additional setup after loading the view.
resultLabel.text = "ASR with Next-gen Kaldi\n\nSee https://github.com/k2-fsa/sherpa-onnx\n\nPress the Start button to run!"
recordBtn.setTitle("Start", for: .normal)
initRecognizer()
initRecorder()
}
@IBAction func onRecordBtnClick(_ sender: UIButton) {
if recordBtn.currentTitle == "Start" {
startRecorder()
recordBtn.setTitle("Stop", for: .normal)
} else {
stopRecorder()
recordBtn.setTitle("Start", for: .normal)
}
}
func initRecognizer() {
// Please select one model that is best suitable for you.
//
// You can also modify Model.swift to add new pre-trained models from
// https://k2-fsa.github.io/sherpa/onnx/pretrained_models/index.html
// let modelConfig = getBilingualStreamZhEnZipformer20230220()
// let modelConfig = getZhZipformer20230615()
// let modelConfig = getEnZipformer20230626()
let modelConfig = getBilingualStreamingZhEnParaformer()
let featConfig = sherpaOnnxFeatureConfig(
sampleRate: 16000,
featureDim: 80)
var config = sherpaOnnxOnlineRecognizerConfig(
featConfig: featConfig,
modelConfig: modelConfig,
enableEndpoint: true,
rule1MinTrailingSilence: 2.4,
rule2MinTrailingSilence: 0.8,
rule3MinUtteranceLength: 30,
decodingMethod: "greedy_search",
maxActivePaths: 4
)
recognizer = SherpaOnnxRecognizer(config: &config)
}
func initRecorder() {
print("init recorder")
audioEngine = AVAudioEngine()
let inputNode = self.audioEngine?.inputNode
let bus = 0
let inputFormat = inputNode?.outputFormat(forBus: bus)
let outputFormat = AVAudioFormat(
commonFormat: .pcmFormatFloat32,
sampleRate: 16000, channels: 1,
interleaved: false)!
let converter = AVAudioConverter(from: inputFormat!, to: outputFormat)!
inputNode!.installTap(
onBus: bus,
bufferSize: 1024,
format: inputFormat
) {
(buffer: AVAudioPCMBuffer, when: AVAudioTime) in
var newBufferAvailable = true
let inputCallback: AVAudioConverterInputBlock = {
inNumPackets, outStatus in
if newBufferAvailable {
outStatus.pointee = .haveData
newBufferAvailable = false
return buffer
} else {
outStatus.pointee = .noDataNow
return nil
}
}
let convertedBuffer = AVAudioPCMBuffer(
pcmFormat: outputFormat,
frameCapacity:
AVAudioFrameCount(outputFormat.sampleRate)
* buffer.frameLength
/ AVAudioFrameCount(buffer.format.sampleRate))!
var error: NSError?
let _ = converter.convert(
to: convertedBuffer,
error: &error, withInputFrom: inputCallback)
// TODO(fangjun): Handle status != haveData
let array = convertedBuffer.array()
if !array.isEmpty {
self.recognizer.acceptWaveform(samples: array)
while (self.recognizer.isReady()){
self.recognizer.decode()
}
let isEndpoint = self.recognizer.isEndpoint()
let text = self.recognizer.getResult().text
if !text.isEmpty && self.lastSentence != text {
self.lastSentence = text
self.updateLabel()
print(text)
}
if isEndpoint {
if !text.isEmpty {
let tmp = self.lastSentence
self.lastSentence = ""
self.sentences.append(tmp)
}
self.recognizer.reset()
}
}
}
}
func startRecorder() {
lastSentence = ""
sentences = []
do {
try self.audioEngine?.start()
} catch let error as NSError {
print("Got an error starting audioEngine: \(error.domain), \(error)")
}
print("started")
}
func stopRecorder() {
audioEngine?.stop()
print("stopped")
}
}