导入语音识别和翻译机器框架,可以按照以下步骤操作:
步骤 1: 导入 Speech.framework
- 打开 Xcode,选择你的项目。
- 在项目导航栏中,点击项目名称(非 Targets)。
- 在 “General” 选项卡下,找到 “Frameworks, Libraries, and Embedded Content”。
- 点击 “+” 按钮,在弹出的框架列表中选择
Speech.framework,点击 “Add” 添加。
步骤 2: 配置 Info.plist
请注意,在使用语音识别和翻译机器框架之前,您需要在Info.plist文件中请求用户授权以访问语音识别和麦克风。可以通过添加以下键和值来完成此操作:
<key>NSSpeechRecognitionUsageDescription</key>
<string>此应用需要语音识别功能以将语音转换为文字。</string>
<key>NSMicrophoneUsageDescription</key>
<string>此应用需要访问麦克风以录制语音。</string>
步骤 3: 实现语音识别与翻译
######在需要翻译的代码中,使用以下代码示例进行调用:
import Foundation
import Speech
import AVFoundation
class SpeechTranslationService {
private let speechRecognizer = SFSpeechRecognizer(locale: Locale(identifier: "zh-CN"))
private let audioEngine = AVAudioEngine()
private var recognitionRequest: SFSpeechAudioBufferRecognitionRequest?
private var recognitionTask: SFSpeechRecognitionTask?
// 请求语音识别授权
func requestAuthorization(completion: @escaping (Bool) -> Void) {
SFSpeechRecognizer.requestAuthorization { status in
DispatchQueue.main.async {
completion(status == .authorized)
}
}
}
// 从音频文件识别语音
func recognizeSpeech(from url: URL, completion: @escaping (Result<String, Error>) -> Void) {
guard let recognizer = speechRecognizer, recognizer.isAvailable else {
completion(.failure(NSError(domain: "", code: -1, userInfo: [NSLocalizedDescriptionKey: "语音识别不可用"])))
return
}
let request = SFSpeechURLRecognitionRequest(url: url)
recognitionTask = recognizer.recognitionTask(with: request) { result, error in
if let error = error {
completion(.failure(error))
return
}
guard let result = result else { return }
let transcript = result.bestTranscription.formattedString
completion(.success(transcript))
}
}
// 实时麦克风输入识别(示例)
func startLiveRecognition(completion: @escaping (Result<String, Error>) -> Void) {
recognitionRequest = SFSpeechAudioBufferRecognitionRequest()
guard let request = recognitionRequest else { return }
recognitionTask = speechRecognizer?.recognitionTask(with: request) { result, error in
if let error = error {
completion(.failure(error))
return
}
guard let result = result else { return }
let transcript = result.bestTranscription.formattedString
completion(.success(transcript))
}
let recordingFormat = audioEngine.inputNode.outputFormat(forBus: 0)
audioEngine.inputNode.installTap(onBus: 0, bufferSize: 1024, format: recordingFormat) { buffer, _ in
request.append(buffer)
}
audioEngine.prepare()
try? audioEngine.start()
}
func stopLiveRecognition() {
audioEngine.stop()
recognitionRequest?.endAudio()
recognitionTask?.cancel()
audioEngine.inputNode.removeTap(onBus: 0)
}
// 假设的翻译方法(需集成第三方 API)
func translate(text: String, from sourceLang: String = "zh-CN", to targetLang: String = "en", completion: @escaping (Result<String, Error>) -> Void) {
// 示例:调用第三方翻译 API(需自行实现)
// 这里仅为占位符,实际需使用 HTTP 请求
let mockTranslation = "Translated: \(text)" // 替换为真实翻译逻辑
completion(.success(mockTranslation))
}
}
// 使用示例
let service = SpeechTranslationService()
// 请求授权
service.requestAuthorization { authorized in
if authorized {
print("授权成功")
// 从文件识别语音
let audioURL = Bundle.main.url(forResource: "sample", withExtension: "m4a")!
service.recognizeSpeech(from: audioURL) { result in
switch result {
case .success(let text):
print("识别结果: \(text)")
// 翻译
service.translate(text: text) { translationResult in
switch translationResult {
case .success(let translatedText):
print("翻译结果: \(translatedText)")
case .failure(let error):
print("翻译失败: \(error.localizedDescription)")
}
}
case .failure(let error):
print("识别失败: \(error.localizedDescription)")
}
}
// 或者启动实时识别
// service.startLiveRecognition { result in ... }
} else {
print("授权失败")
}
}
注意事项
- 音频文件:确保 audioURL 指向有效的音频文件(如 .m4a 或 .wav)。
- 翻译实现:由于 iOS 无内置翻译框架,需集成第三方服务(如 Google Cloud Translation API)。上述代码中的 translate 方法仅为占位符,实际开发中需替换为真实 API 调用。
- 权限检查:实时识别需确保麦克风权限已授权。
- 错误处理:代码中增加了基本的错误处理逻辑,提升健壮性。