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Agent Skill · 待分类

speech-recognition(语音识别)

用于辅助音频、音乐、语音转写、语音合成或声音素材处理。它适合让 Agent 生成配乐说明、整理音频流程、调用语音工具或处理播客和视频配音素材。使用时需要确认输入音频来源、输出格式、时长和模型限制;涉及人声克隆、版权音乐或公开发布时,应先核对授权和合规边界。

speech-recognition 是待分类类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描已通过,按安装量在待分类类的 11,209 个 Skill 里排第 239。

总安装 26,928周安装 1,099GitHub Stars 478下载 8,624核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:speech-recognition(语音识别)
来源仓库:https://github.com/dpearson2699/swift-ios-skills
仓库路径:skills/speech-recognition
安装命令:
npx skills add https://github.com/dpearson2699/swift-ios-skills --skill speech-recognition
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/dpearson2699/swift-ios-skills --skill speech-recognition

这个 Skill 是做什么的

这个 Skill 的分类还没最终确定,用法以来源仓库的说明为准。

speech-recognition 利用 Apple Speech 框架实现实时与离线语音转文字功能。适用于语音助手、会议记录或播客字幕生成等需要高精度本地识别的场景。支持 SFSpeechRecognizer 与新版 SpeechAnalyzer API,适配不同 iOS 版本与开发风格。

需用户授权麦克风权限,长音频建议使用分块处理避免内存溢出。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/speech-recognition

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/dpearson2699/swift-ios-skills --skill speech-r…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

speech-recognition 怎么安装?

在终端执行 npx skills add https://github.com/dpearson2699/swift-ios-skills --skill speech-recognition。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

speech-recognition 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

speech-recognition 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

speech-recognition 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

speech-recognition 用的人多吗?

公开数据是累计安装 26,928 次,近一周安装 1,099 次,下载 8,624 次,GitHub 478 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

speech-recognition 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理待分类类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

待分类类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
infsh-cli

infsh CLI · Codex、Claude

4,374,576382权限未标注未明确未收录
ai-video-generation

AI 视频生成 · Codex、Claude

4,313,376382调用外部服务未明确有提醒
lark-openapi-explorer

云雀 OpenAPI 浏览器 · Codex、Claude

2,064,1209,011需要联网未明确有提醒
lark-workflow-standup-report

Lark 工作流程站立报告 · Codex、Claude

2,041,6328,978需要联网未明确通过
use-my-browser

使用我的浏览器 · Codex、Claude

1,848,49140操作浏览器未明确未通过
speech-recognition

语音识别 · 本页

26,928478需要联网未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Speech Recognition

Transcribe live and pre-recorded audio to text using Apple's Speech framework. Covers SFSpeechRecognizer (iOS 10+) and the new SpeechAnalyzer API (iOS 26+).

Contents

SpeechAnalyzer (iOS 26+)

SpeechAnalyzer is an actor-based API introduced in iOS 26 that replaces SFSpeechRecognizer for new projects. It uses Swift concurrency, AsyncSequence for results, and supports modular analysis via SpeechTranscriber.

Basic transcription with SpeechAnalyzer

import Speech

// 1. Create a transcriber module
guard let locale = SpeechTranscriber.supportedLocale(
    equivalentTo: Locale.current
) else { return }
let transcriber = SpeechTranscriber(locale: locale, preset: .offlineTranscription)

// 2. Ensure assets are installed
if let request = try await AssetInventory.assetInstallationRequest(
    supporting: [transcriber]
) {
    try await request.downloadAndInstall()
}

// 3. Create input stream and analyzer
let (inputSequence, inputBuilder) = AsyncStream.makeStream(of: AnalyzerInput.self)
let audioFormat = await SpeechAnalyzer.bestAvailableAudioFormat(
    compatibleWith: [transcriber]
)
let analyzer = SpeechAnalyzer(modules: [transcriber])

// 4. Feed audio buffers (from AVAudioEngine or file)
Task {
    // Append PCM buffers converted to audioFormat
    let pcmBuffer: AVAudioPCMBuffer = // ... your audio buffer
    inputBuilder.yield(AnalyzerInput(buffer: pcmBuffer))
    inputBuilder.finish()
}

// 5. Consume results
Task {
    for try await result in transcriber.results {
        let text = String(result.text.characters)
        print(text)
    }
}

// 6. Run analysis
let lastSampleTime = try await analyzer.analyzeSequence(inputSequence)

// 7. Finalize
if let lastSampleTime {
    try await analyzer.finalizeAndFinish(through: lastSampleTime)
} else {
    try analyzer.cancelAndFinishNow()
}

Transcribing an audio file with SpeechAnalyzer

let transcriber = SpeechTranscriber(locale: locale, preset: .offlineTranscription)
let audioFile = try AVAudioFile(forReading: fileURL)
let analyzer = SpeechAnalyzer(
    inputAudioFile: audioFile, modules: [transcriber], finishAfterFile: true
)
for try await result in transcriber.results {
    print(String(result.text.characters))
}

Key differences from SFSpeechRecognizer

FeatureSFSpeechRecognizerSpeechAnalyzer
ConcurrencyCallbacks/delegatesasync/await + AsyncSequence
Typeclassactor
ModulesMonolithicComposable (SpeechTranscriber, SpeechDetector)
Audio inputappend(_:) on requestAsyncStream<AnalyzerInput>
AvailabilityiOS 10+iOS 26+
On-devicerequiresOnDeviceRecognitionAsset-based via AssetInventory

SFSpeechRecognizer Setup

Creating a recognizer with locale

import Speech

// Default locale (user's current language)
let recognizer = SFSpeechRecognizer()

// Specific locale
let recognizer = SFSpeechRecognizer(locale: Locale(identifier: "en-US"))

// Check if recognition is available for this locale
guard let recognizer, recognizer.isAvailable else {
    print("Speech recognition not available")
    return
}

Monitoring availability changes

final class SpeechManager: NSObject, SFSpeechRecognizerDelegate {
    private let recognizer = SFSpeechRecognizer()!

    override init() {
        super.init()
        recognizer.delegate = self
    }

    func speechRecognizer(
        _ speechRecognizer: SFSpeechRecognizer,
        availabilityDidChange available: Bool
    ) {
        // Update UI — disable record button when unavailable
    }
}

Authorization

Request both speech recognition and microphone permissions before starting live transcription. Add these keys to Info.plist:

  • NSSpeechRecognitionUsageDescription
  • NSMicrophoneUsageDescription
import Speech
import AVFoundation

func requestPermissions() async -> Bool {
    let speechStatus = await withCheckedContinuation { continuation in
        SFSpeechRecognizer.requestAuthorization { status in
            continuation.resume(returning: status)
        }
    }
    guard speechStatus == .authorized else { return false }

    let micStatus: Bool
    if #available(iOS 17, *) {
        micStatus = await AVAudioApplication.requestRecordPermission()
    } else {
        micStatus = await withCheckedContinuation { continuation in
            AVAudioSession.sharedInstance().requestRecordPermission { granted in
                continuation.resume(returning: granted)
            }
        }
    }
    return micStatus
}

Live Microphone Transcription

The standard pattern: AVAudioEngine captures microphone audio → buffers are appended to SFSpeechAudioBufferRecognitionRequest → results stream in.

import Speech
import AVFoundation

final class LiveTranscriber {
    private let recognizer = SFSpeechRecognizer(locale: Locale(identifier: "en-US"))!
    private let audioEngine = AVAudioEngine()
    private var recognitionRequest: SFSpeechAudioBufferRecognitionRequest?
    private var recognitionTask: SFSpeechRecognitionTask?

    func startTranscribing() throws {
        // Cancel any in-progress task
        recognitionTask?.cancel()
        recognitionTask = nil

        // Configure audio session
        let audioSession = AVAudioSession.sharedInstance()
        try audioSession.setCategory(.record, mode: .measurement, options: .duckOthers)
        try audioSession.setActive(true, options: .notifyOthersOnDeactivation)

        // Create request
        let request = SFSpeechAudioBufferRecognitionRequest()
        request.shouldReportPartialResults = true
        self.recognitionRequest = request

        // Start recognition task
        recognitionTask = recognizer.recognitionTask(with: request) { result, error in
            if let result {
                let text = result.bestTranscription.formattedString
                print("Transcription: \(text)")

                if result.isFinal {
                    self.stopTranscribing()
                }
            }
            if let error {
                print("Recognition error: \(error)")
                self.stopTranscribing()
            }
        }

        // Install audio tap
        let inputNode = audioEngine.inputNode
        let recordingFormat = inputNode.outputFormat(forBus: 0)
        inputNode.installTap(onBus: 0, bufferSize: 1024, format: recordingFormat) {
            buffer, _ in
            request.append(buffer)
        }

        audioEngine.prepare()
        try audioEngine.start()
    }

    func stopTranscribing() {
        audioEngine.stop()
        audioEngine.inputNode.removeTap(onBus: 0)
        recognitionRequest?.endAudio()
        recognitionRequest = nil
        recognitionTask?.cancel()
        recognitionTask = nil
    }
}

Pre-Recorded Audio File Recognition

Use SFSpeechURLRecognitionRequest for audio files on disk:

func transcribeFile(at url: URL) async throws -> String {
    guard let recognizer = SFSpeechRecognizer(), recognizer.isAvailable else {
        throw SpeechError.unavailable
    }
    let request = SFSpeechURLRecognitionRequest(url: url)
    request.shouldReportPartialResults = false

    return try await withCheckedThrowingContinuation { continuation in
        recognizer.recognitionTask(with: request) { result, error in
            if let error {
                continuation.resume(throwing: error)
            } else if let result, result.isFinal {
                continuation.resume(
                    returning: result.bestTranscription.formattedString
                )
            }
        }
    }
}

On-Device vs Server Recognition

On-device recognition (iOS 13+) works offline but supports fewer locales:

let recognizer = SFSpeechRecognizer(locale: Locale(identifier: "en-US"))!

// Check if on-device is supported for this locale
if recognizer.supportsOnDeviceRecognition {
    let request = SFSpeechAudioBufferRecognitionRequest()
    request.requiresOnDeviceRecognition = true  // Force on-device
}
Tip: On-device recognition avoids network latency and the one-minute audio limit imposed by server-based recognition. However, accuracy may be lower and not all locales are supported. Check supportsOnDeviceRecognition before forcing on-device mode.

Handling Results

Partial vs final results

let request = SFSpeechAudioBufferRecognitionRequest()
request.shouldReportPartialResults = true  // default is true

recognizer.recognitionTask(with: request) { result, error in
    guard let result else { return }

    if result.isFinal {
        // Final transcription — recognition is complete
        let final = result.bestTranscription.formattedString
    } else {
        // Partial result — may change as more audio is processed
        let partial = result.bestTranscription.formattedString
    }
}

Accessing alternative transcriptions and confidence

recognizer.recognitionTask(with: request) { result, error in
    guard let result else { return }

    // Best transcription
    let best = result.bestTranscription

    // All alternatives (sorted by confidence, descending)
    for transcription in result.transcriptions {
        for segment in transcription.segments {
            print("\(segment.substring): \(segment.confidence)")
        }
    }
}

Adding punctuation (iOS 16+)

let request = SFSpeechAudioBufferRecognitionRequest()
request.addsPunctuation = true

Contextual strings

Improve recognition of domain-specific terms:

let request = SFSpeechAudioBufferRecognitionRequest()
request.contextualStrings = ["SwiftUI", "Xcode", "CloudKit"]

Common Mistakes

Not requesting both speech and microphone authorization

// ❌ DON'T: Only request speech authorization for live audio
SFSpeechRecognizer.requestAuthorization { status in
    // Missing microphone permission — audio engine will fail
    self.startRecording()
}

// ✅ DO: Request both permissions before recording
SFSpeechRecognizer.requestAuthorization { status in
    guard status == .authorized else { return }
    AVAudioSession.sharedInstance().requestRecordPermission { granted in
        guard granted else { return }
        self.startRecording()
    }
}

Not handling availability changes

// ❌ DON'T: Assume recognizer stays available after initial check
let recognizer = SFSpeechRecognizer()!
// Recognition may fail if network drops or locale changes

// ✅ DO: Monitor availability via delegate
recognizer.delegate = self
func speechRecognizer(
    _ speechRecognizer: SFSpeechRecognizer,
    availabilityDidChange available: Bool
) {
    recordButton.isEnabled = available
}

Not stopping the audio engine when recognition ends

// ❌ DON'T: Leave audio engine running after recognition finishes
recognizer.recognitionTask(with: request) { result, error in
    if result?.isFinal == true {
        // Audio engine still running, wasting resources and battery
    }
}

// ✅ DO: Clean up all audio resources
recognizer.recognitionTask(with: request) { result, error in
    if result?.isFinal == true || error != nil {
        self.audioEngine.stop()
        self.audioEngine.inputNode.removeTap(onBus: 0)
        self.recognitionRequest?.endAudio()
        self.recognitionRequest = nil
    }
}

Assuming on-device recognition is available for all locales

// ❌ DON'T: Force on-device without checking support
let request = SFSpeechAudioBufferRecognitionRequest()
request.requiresOnDeviceRecognition = true // May silently fail

// ✅ DO: Check support before requiring on-device
if recognizer.supportsOnDeviceRecognition {
    request.requiresOnDeviceRecognition = true
} else {
    // Fall back to server-based or inform user
}

Not handling the one-minute recognition limit

// ❌ DON'T: Start one long continuous recognition session
func startRecording() {
    // This will be cut off after ~60 seconds (server-based)
}

// ✅ DO: Restart recognition when approaching the limit
func startRecording() {
    // Use a timer to restart before the limit
    recognitionTimer = Timer.scheduledTimer(withTimeInterval: 55, repeats: false) {
        [weak self] _ in
        self?.restartRecognition()
    }
}

Creating multiple simultaneous recognition tasks

// ❌ DON'T: Start a new task without canceling the previous one
func startRecording() {
    recognitionTask = recognizer.recognitionTask(with: request) { ... }
    // Previous task is still running — undefined behavior
}

// ✅ DO: Cancel existing task before creating a new one
func startRecording() {
    recognitionTask?.cancel()
    recognitionTask = nil
    recognitionTask = recognizer.recognitionTask(with: request) { ... }
}

Review Checklist

  • NSSpeechRecognitionUsageDescription is in Info.plist
  • NSMicrophoneUsageDescription is in Info.plist (if using live audio)
  • Authorization is requested before starting recognition
  • SFSpeechRecognizerDelegate is set to handle availabilityDidChange
  • Audio engine is stopped and tap removed when recognition ends
  • recognitionRequest.endAudio() is called when done recording
  • Previous recognitionTask is canceled before starting a new one
  • supportsOnDeviceRecognition is checked before requiring on-device mode
  • Partial results are handled separately from final (isFinal) results
  • One-minute limit is accounted for in server-based recognition
  • For iOS 26+: AssetInventory assets are installed before using SpeechAnalyzer
  • For iOS 26+: SpeechTranscriber.supportedLocale(equivalentTo:) is checked

References

平台分布

Codex

36.04%
按下载量换算3,108

Claude

30.95%
按下载量换算2,669

Cursor

19.87%
按下载量换算1,714

Gemini CLI

9.13%
按下载量换算787

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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