Android拼读打分系统技术方案

1. 系统概述

1.1 系统目标

开发一个基于Android的汉字、英文单词拼读打分系统，通过语音识别技术评估用户发音准确性，提供实时反馈和评分。

1.2 核心功能

• 汉字发音评估：将用户语音转换为文本，与标准拼音对比打分
• 英文单词发音评估：将用户语音转换为文本，与标准音标对比打分
• 实时语音识别和评分
• 发音错误分析和改进建议

2. 技术架构

2.1 整体架构

┌─────────────────────────────────────────┐
│                UI层                      │
│  ┌─────────────┐  ┌─────────────────┐   │
│  │  录音界面    │  │   评分结果界面   │   │
│  └─────────────┘  └─────────────────┘   │
└─────────────────────────────────────────┘
                    │
┌─────────────────────────────────────────┐
│              业务逻辑层                   │
│  ┌─────────────┐  ┌─────────────────┐   │
│  │ 语音识别管理 │  │   评分算法管理   │   │
│  └─────────────┘  └─────────────────┘   │
└─────────────────────────────────────────┘
                    │
┌─────────────────────────────────────────┐
│              核心服务层                   │
│  ┌─────────────┐  ┌─────────────────┐   │
│  │ Vosk引擎    │  │ 拼音/音标转换   │   │
│  └─────────────┘  └─────────────────┘   │
└─────────────────────────────────────────┘

2.2 技术选型

2.2.1 语音识别引擎

• Vosk: 轻量级离线语音识别库
• 模型选择: vosk-model-small-zh-cn-0.22 (中文) + vosk-model-small-en-us-0.15 (英文)
• 优势:
  • 完全离线，无需网络
  • 模型体积小（约40MB）
  • 支持中英文混合识别
  • 低延迟，适合实时应用

2.2.2 开发框架

• 语言: Kotlin + Java
• 架构: MVVM + Repository模式
• UI框架: Jetpack Compose
• 依赖注入: Hilt
• 异步处理: Coroutines + Flow
• 音标数据库: CMC (Cambridge English Pronouncing Dictionary)

3. 核心模块设计

3.1 语音识别模块 (SpeechRecognitionModule)

3.1.1 功能职责

• 音频录制和预处理
• Vosk引擎初始化和配置
• 实时语音识别
• 识别结果回调

3.1.2 关键类设计

// 语音识别管理器
class SpeechRecognitionManager {
    private var voskModel: Model? = null
    private var recognizer: Recognizer? = null
    private var audioRecorder: AudioRecorder? = null
    
    suspend fun initializeModel(language: Language)
    fun startRecognition()
    fun stopRecognition()
    fun pauseRecognition()
    fun resumeRecognition()
}

// 音频录制器
class AudioRecorder {
    private var mediaRecorder: MediaRecorder? = null
    private var audioThread: Thread? = null
    
    fun startRecording()
    fun stopRecording()
    fun pauseRecording()
    fun resumeRecording()
}

// 语言枚举
enum class Language {
    CHINESE, ENGLISH, MIXED
}

3.2 拼音转换模块 (PinyinModule)

3.2.1 功能职责

• 汉字转拼音
• 拼音标准化处理
• 声调处理

3.2.2 关键类设计

// 拼音转换器
class PinyinConverter {
    fun convertToPinyin(chineseText: String): List<String>
    fun normalizePinyin(pinyin: String): String
    fun removeTones(pinyin: String): String
    fun getTone(pinyin: String): Int
}

// 拼音数据模型
data class PinyinInfo(
    val original: String,
    val normalized: String,
    val tone: Int,
    val withoutTone: String
)

3.3 音标转换模块 (PhoneticModule)

3.3.1 功能职责

• 英文单词转音标
• 音标标准化
• 音标对比算法

3.3.2 关键类设计

// 音标转换器
class PhoneticConverter {
    fun convertToPhonetic(englishWord: String): String
    fun normalizePhonetic(phonetic: String): String
    fun splitPhonetic(phonetic: String): List<String>
}

// 音标数据模型
data class PhoneticInfo(
    val word: String,
    val phonetic: String,
    val normalized: String,
    val syllables: List<String>
)

3.4 评分算法模块 (ScoringModule)

3.4.1 功能职责

• 拼音对比和评分
• 音标对比和评分
• 综合评分计算
• 错误分析

3.4.2 关键类设计

// 评分算法
class PronunciationScorer {
    fun scoreChinese(recognized: String, standard: String): ScoreResult
    fun scoreEnglish(recognized: String, standard: String): ScoreResult
    fun calculateSimilarity(text1: String, text2: String): Float
}

// 评分结果
data class ScoreResult(
    val score: Int, // 0-100
    val accuracy: Float, // 0.0-1.0
    val errors: List<PronunciationError>,
    val suggestions: List<String>
)

// 发音错误
data class PronunciationError(
    val type: ErrorType,
    val position: Int,
    val expected: String,
    val actual: String,
    val severity: ErrorSeverity
)

enum class ErrorType {
    TONE_ERROR, // 声调错误
    PHONEME_ERROR, // 音素错误
    MISSING_SOUND, // 缺失音
    EXTRA_SOUND // 多余音
}

enum class ErrorSeverity {
    LOW, MEDIUM, HIGH
}

4. 详细实现方案

4.1 Vosk集成方案

4.1.1 依赖配置

// build.gradle (Module: app)
dependencies {
    implementation 'com.alphacephei:vosk-android:0.3.45'
    implementation 'org.jetbrains.kotlinx:kotlinx-coroutines-android:1.6.4'
    implementation 'androidx.lifecycle:lifecycle-viewmodel-ktx:2.6.2'
    implementation 'androidx.lifecycle:lifecycle-livedata-ktx:2.6.2'
}

4.1.2 模型集成

// 模型管理器
class VoskModelManager {
    companion object {
        private const val CHINESE_MODEL_PATH = "vosk-model-small-zh-cn-0.22"
        private const val ENGLISH_MODEL_PATH = "vosk-model-small-en-us-0.15"
    }
    
    suspend fun loadModel(language: Language): Model {
        return withContext(Dispatchers.IO) {
            val modelPath = when (language) {
                Language.CHINESE -> CHINESE_MODEL_PATH
                Language.ENGLISH -> ENGLISH_MODEL_PATH
                Language.MIXED -> CHINESE_MODEL_PATH // 默认使用中文模型
            }
            Model(File(context.filesDir, modelPath).absolutePath)
        }
    }
}

4.1.3 实时识别实现

class RealtimeSpeechRecognizer {
    private var recognizer: Recognizer? = null
    private val audioQueue = mutableListOf<ByteArray>()
    private var isRecognizing = false
    
    fun startRecognition(model: Model, sampleRate: Float = 16000f) {
        recognizer = Recognizer(model, sampleRate)
        isRecognizing = true
        
        // 启动音频处理线程
        Thread {
            while (isRecognizing) {
                if (audioQueue.isNotEmpty()) {
                    val audioData = audioQueue.removeAt(0)
                    val result = recognizer?.acceptWaveForm(audioData, audioData.size)
                    
                    if (result != null && result.isNotEmpty()) {
                        val jsonResult = JSONObject(result)
                        val text = jsonResult.getString("text")
                        onRecognitionResult(text)
                    }
                }
            }
        }.start()
    }
    
    fun addAudioData(audioData: ByteArray) {
        if (isRecognizing) {
            audioQueue.add(audioData)
        }
    }
    
    private fun onRecognitionResult(text: String) {
        // 回调识别结果
    }
}

4.2 拼音转换实现

4.2.1 使用TinyPinyin库

dependencies {
    implementation 'io.github.biezhi:TinyPinyin:2.0.3'
}

4.2.2 拼音转换实现

class PinyinConverter {
    init {
        // 初始化TinyPinyin
        TinyPinyin.init()
    }
    
    fun convertToPinyin(chineseText: String): List<PinyinInfo> {
        return chineseText.map { char ->
            val pinyin = TinyPinyin.toPinyin(char)
            PinyinInfo(
                original = pinyin,
                normalized = normalizePinyin(pinyin),
                tone = extractTone(pinyin),
                withoutTone = removeTone(pinyin)
            )
        }
    }
    
    private fun normalizePinyin(pinyin: String): String {
        // 标准化拼音格式
        return pinyin.lowercase()
            .replace("ü", "v")
            .replace("ê", "e")
    }
    
    private fun extractTone(pinyin: String): Int {
        // 提取声调
        val toneMap = mapOf(
            "ā" to 1, "á" to 2, "ǎ" to 3, "à" to 4,
            "ē" to 1, "é" to 2, "ě" to 3, "è" to 4,
            // ... 其他声调映射
        )
        
        for ((toneChar, tone) in toneMap) {
            if (pinyin.contains(toneChar)) {
                return tone
            }
        }
        return 0 // 轻声
    }
    
    private fun removeTone(pinyin: String): String {
        // 移除声调符号
        val toneMap = mapOf(
            "ā" to "a", "á" to "a", "ǎ" to "a", "à" to "a",
            "ē" to "e", "é" to "e", "ě" to "e", "è" to "e",
            // ... 其他声调映射
        )
        
        var result = pinyin
        for ((toneChar, baseChar) in toneMap) {
            result = result.replace(toneChar, baseChar)
        }
        return result
    }
}

4.3 音标转换实现

4.3.1 CMC音标数据库集成

// CMC音标数据库管理器
class CMCPhoneticDatabase {
    private val cmcDatabase: CMCDataBase
    private val phoneticCache = mutableMapOf<String, String>()
    
    init {
        // 初始化CMC数据库
        cmcDatabase = CMCDataBase.getInstance(context)
    }
    
    fun getPhonetic(word: String): String? {
        val lowerWord = word.lowercase()
        
        // 先从缓存查找
        phoneticCache[lowerWord]?.let { return it }
        
        // 从CMC数据库查询
        val phonetic = cmcDatabase.getPhonetic(lowerWord)
        if (phonetic != null) {
            phoneticCache[lowerWord] = phonetic
        }
        
        return phonetic
    }
    
    fun getMultiplePronunciations(word: String): List<String> {
        return cmcDatabase.getMultiplePronunciations(word.lowercase())
    }
    
    fun normalizePhonetic(phonetic: String): String {
        return phonetic.replace("/", "")
            .replace("ˈ", "") // 主重音
            .replace("ˌ", "") // 次重音
            .replace("ː", "") // 长音符号
            .lowercase()
    }
    
    fun getPhoneticVariants(word: String): List<PhoneticVariant> {
        return cmcDatabase.getPhoneticVariants(word.lowercase())
    }
}

// CMC音标变体数据模型
data class PhoneticVariant(
    val phonetic: String,
    val region: String, // 如 "US", "UK", "AU"
    val frequency: Float, // 使用频率
    val isPrimary: Boolean // 是否为主要发音
)

4.3.2 CMC音标转换器

class CMCPhoneticConverter {
    private val cmcDatabase = CMCPhoneticDatabase()
    
    fun convertToPhonetic(englishWord: String): PhoneticInfo? {
        val phonetic = cmcDatabase.getPhonetic(englishWord) ?: return null
        
        return PhoneticInfo(
            word = englishWord,
            phonetic = phonetic,
            normalized = cmcDatabase.normalizePhonetic(phonetic),
            syllables = splitIntoSyllables(phonetic),
            variants = cmcDatabase.getPhoneticVariants(englishWord)
        )
    }
    
    fun getBestPhoneticMatch(recognizedWord: String, targetWord: String): PhoneticMatch? {
        val targetPhonetics = cmcDatabase.getMultiplePronunciations(targetWord)
        val recognizedPhonetic = cmcDatabase.getPhonetic(recognizedWord)
        
        if (recognizedPhonetic == null || targetPhonetics.isEmpty()) {
            return null
        }
        
        var bestMatch: PhoneticMatch? = null
        var bestScore = 0f
        
        for (targetPhonetic in targetPhonetics) {
            val score = calculatePhoneticSimilarity(
                cmcDatabase.normalizePhonetic(recognizedPhonetic),
                cmcDatabase.normalizePhonetic(targetPhonetic)
            )
            
            if (score > bestScore) {
                bestScore = score
                bestMatch = PhoneticMatch(
                    recognizedPhonetic = recognizedPhonetic,
                    targetPhonetic = targetPhonetic,
                    similarity = score
                )
            }
        }
        
        return bestMatch
    }
    
    private fun splitIntoSyllables(phonetic: String): List<String> {
        // 根据重音符号分割音节
        return phonetic.split("ˈ", "ˌ")
            .filter { it.isNotEmpty() }
            .map { it.trim() }
    }
    
    private fun calculatePhoneticSimilarity(phonetic1: String, phonetic2: String): Float {
        // 使用编辑距离算法计算相似度
        val distance = levenshteinDistance(phonetic1, phonetic2)
        val maxLength = maxOf(phonetic1.length, phonetic2.length)
        return if (maxLength == 0) 1.0f else (maxLength - distance).toFloat() / maxLength
    }
}

// 音标匹配结果
data class PhoneticMatch(
    val recognizedPhonetic: String,
    val targetPhonetic: String,
    val similarity: Float
)

// 扩展的PhoneticInfo
data class PhoneticInfo(
    val word: String,
    val phonetic: String,
    val normalized: String,
    val syllables: List<String>,
    val variants: List<PhoneticVariant> = emptyList()
)

4.4 评分算法实现

4.4.1 中文评分算法

class ChineseScoringAlgorithm {
    fun score(recognized: String, standard: String): ScoreResult {
        val recognizedPinyin = PinyinConverter().convertToPinyin(recognized)
        val standardPinyin = PinyinConverter().convertToPinyin(standard)
        
        val errors = mutableListOf<PronunciationError>()
        var correctCount = 0
        val totalCount = standardPinyin.size
        
        for (i in standardPinyin.indices) {
            if (i < recognizedPinyin.size) {
                val recognizedP = recognizedPinyin[i]
                val standardP = standardPinyin[i]
                
                val similarity = calculatePinyinSimilarity(recognizedP, standardP)
                if (similarity >= 0.8f) {
                    correctCount++
                } else {
                    errors.add(analyzePinyinError(recognizedP, standardP, i))
                }
            } else {
                errors.add(PronunciationError(
                    type = ErrorType.MISSING_SOUND,
                    position = i,
                    expected = standardPinyin[i].original,
                    actual = "",
                    severity = ErrorSeverity.HIGH
                ))
            }
        }
        
        val score = (correctCount * 100) / totalCount
        val accuracy = correctCount.toFloat() / totalCount
        
        return ScoreResult(
            score = score,
            accuracy = accuracy,
            errors = errors,
            suggestions = generateSuggestions(errors)
        )
    }
    
    private fun calculatePinyinSimilarity(pinyin1: PinyinInfo, pinyin2: PinyinInfo): Float {
        val baseSimilarity = if (pinyin1.withoutTone == pinyin2.withoutTone) 0.7f else 0.0f
        val toneSimilarity = if (pinyin1.tone == pinyin2.tone) 0.3f else 0.0f
        return baseSimilarity + toneSimilarity
    }
    
    private fun analyzePinyinError(recognized: PinyinInfo, standard: PinyinInfo, position: Int): PronunciationError {
        return when {
            recognized.withoutTone != standard.withoutTone -> 
                PronunciationError(ErrorType.PHONEME_ERROR, position, standard.original, recognized.original, ErrorSeverity.HIGH)
            recognized.tone != standard.tone -> 
                PronunciationError(ErrorType.TONE_ERROR, position, standard.original, recognized.original, ErrorSeverity.MEDIUM)
            else -> 
                PronunciationError(ErrorType.PHONEME_ERROR, position, standard.original, recognized.original, ErrorSeverity.LOW)
        }
    }
}

4.4.2 基于CMC的英文评分算法

class CMCEnglishScoringAlgorithm {
    private val cmcConverter = CMCPhoneticConverter()
    
    fun score(recognized: String, standard: String): ScoreResult {
        // 使用CMC数据库获取最佳音标匹配
        val phoneticMatch = cmcConverter.getBestPhoneticMatch(recognized, standard)
        
        if (phoneticMatch == null) {
            return ScoreResult(
                score = 0, 
                accuracy = 0.0f, 
                errors = listOf(PronunciationError(
                    type = ErrorType.PHONEME_ERROR,
                    position = 0,
                    expected = standard,
                    actual = recognized,
                    severity = ErrorSeverity.HIGH
                )), 
                suggestions = listOf("请检查单词拼写或发音")
            )
        }
        
        val score = (phoneticMatch.similarity * 100).toInt()
        val errors = analyzeCMCPhoneticErrors(phoneticMatch)
        
        return ScoreResult(
            score = score,
            accuracy = phoneticMatch.similarity,
            errors = errors,
            suggestions = generateCMCSuggestions(errors, phoneticMatch)
        )
    }
    
    private fun analyzeCMCPhoneticErrors(phoneticMatch: PhoneticMatch): List<PronunciationError> {
        val errors = mutableListOf<PronunciationError>()
        val recognized = phoneticMatch.recognizedPhonetic
        val target = phoneticMatch.targetPhonetic
        
        // 分析音素级别的错误
        val recognizedPhonemes = splitIntoPhonemes(recognized)
        val targetPhonemes = splitIntoPhonemes(target)
        
        val maxLength = maxOf(recognizedPhonemes.size, targetPhonemes.size)
        
        for (i in 0 until maxLength) {
            val recognizedPhoneme = if (i < recognizedPhonemes.size) recognizedPhonemes[i] else ""
            val targetPhoneme = if (i < targetPhonemes.size) targetPhonemes[i] else ""
            
            when {
                recognizedPhoneme.isEmpty() -> {
                    errors.add(PronunciationError(
                        type = ErrorType.MISSING_SOUND,
                        position = i,
                        expected = targetPhoneme,
                        actual = "",
                        severity = ErrorSeverity.HIGH
                    ))
                }
                targetPhoneme.isEmpty() -> {
                    errors.add(PronunciationError(
                        type = ErrorType.EXTRA_SOUND,
                        position = i,
                        expected = "",
                        actual = recognizedPhoneme,
                        severity = ErrorSeverity.MEDIUM
                    ))
                }
                !isPhonemeSimilar(recognizedPhoneme, targetPhoneme) -> {
                    errors.add(PronunciationError(
                        type = ErrorType.PHONEME_ERROR,
                        position = i,
                        expected = targetPhoneme,
                        actual = recognizedPhoneme,
                        severity = calculatePhonemeErrorSeverity(recognizedPhoneme, targetPhoneme)
                    ))
                }
            }
        }
        
        return errors
    }
    
    private fun splitIntoPhonemes(phonetic: String): List<String> {
        // 根据CMC音标符号分割音素
        val phonemePattern = Regex("[a-zA-Zəɪɛæʌɔʊuːˈˌ]+")
        return phonemePattern.findAll(phonetic)
            .map { it.value }
            .filter { it.isNotEmpty() }
            .toList()
    }
    
    private fun isPhonemeSimilar(phoneme1: String, phoneme2: String): Boolean {
        // 音素相似性判断，考虑音素变体
        val normalized1 = phoneme1.replace("ː", "").replace("ˈ", "").replace("ˌ", "")
        val normalized2 = phoneme2.replace("ː", "").replace("ˈ", "").replace("ˌ", "")
        
        return normalized1 == normalized2 || isPhonemeVariant(normalized1, normalized2)
    }
    
    private fun isPhonemeVariant(phoneme1: String, phoneme2: String): Boolean {
        // 音素变体映射表
        val phonemeVariants = mapOf(
            "i" to listOf("ɪ", "iː"),
            "ɪ" to listOf("i", "iː"),
            "e" to listOf("ɛ", "eɪ"),
            "ɛ" to listOf("e", "eɪ"),
            "æ" to listOf("a", "ɑ"),
            "ɑ" to listOf("a", "æ"),
            "ɔ" to listOf("o", "oʊ"),
            "o" to listOf("ɔ", "oʊ"),
            "ʊ" to listOf("u", "uː"),
            "u" to listOf("ʊ", "uː")
        )
        
        return phonemeVariants[phoneme1]?.contains(phoneme2) == true ||
               phonemeVariants[phoneme2]?.contains(phoneme1) == true
    }
    
    private fun calculatePhonemeErrorSeverity(recognized: String, target: String): ErrorSeverity {
        return when {
            isPhonemeVariant(recognized, target) -> ErrorSeverity.LOW
            recognized.length == target.length -> ErrorSeverity.MEDIUM
            else -> ErrorSeverity.HIGH
        }
    }
    
    private fun generateCMCSuggestions(errors: List<PronunciationError>, phoneticMatch: PhoneticMatch): List<String> {
        val suggestions = mutableListOf<String>()
        
        for (error in errors) {
            when (error.type) {
                ErrorType.MISSING_SOUND -> {
                    suggestions.add("请确保发音包含 '${error.expected}' 音素")
                }
                ErrorType.EXTRA_SOUND -> {
                    suggestions.add("请避免多余的 '${error.actual}' 音素")
                }
                ErrorType.PHONEME_ERROR -> {
                    suggestions.add("'${error.actual}' 应该发音为 '${error.expected}'")
                }
                else -> {
                    suggestions.add("请仔细听标准发音并模仿")
                }
            }
        }
        
        // 添加CMC特定的建议
        if (phoneticMatch.similarity < 0.7f) {
            suggestions.add("建议使用CMC发音指南进行练习")
        }
        
        return suggestions
    }
}

5. 用户界面设计

5.1 主界面设计

@Composable
fun PronunciationScoringScreen() {
    val viewModel: PronunciationViewModel = hiltViewModel()
    val uiState by viewModel.uiState.collectAsState()
    
    Column(
        modifier = Modifier
            .fillMaxSize()
            .padding(16.dp)
    ) {
        // 语言选择
        LanguageSelector(
            selectedLanguage = uiState.selectedLanguage,
            onLanguageChanged = viewModel::selectLanguage
        )
        
        Spacer(modifier = Modifier.height(16.dp))
        
        // 目标文本显示
        TargetTextCard(
            text = uiState.targetText,
            phonetic = uiState.targetPhonetic
        )
        
        Spacer(modifier = Modifier.height(16.dp))
        
        // 录音控制
        RecordingControl(
            isRecording = uiState.isRecording,
            onStartRecording = viewModel::startRecording,
            onStopRecording = viewModel::stopRecording
        )
        
        Spacer(modifier = Modifier.height(16.dp))
        
        // 识别结果显示
        RecognitionResultCard(
            recognizedText = uiState.recognizedText,
            isVisible = uiState.recognizedText.isNotEmpty()
        )
        
        Spacer(modifier = Modifier.height(16.dp))
        
        // 评分结果
        ScoreResultCard(
            scoreResult = uiState.scoreResult,
            isVisible = uiState.scoreResult != null
        )
    }
}

5.2 录音控制组件

@Composable
fun RecordingControl(
    isRecording: Boolean,
    onStartRecording: () -> Unit,
    onStopRecording: () -> Unit
) {
    Card(
        modifier = Modifier.fillMaxWidth(),
        elevation = CardDefaults.cardElevation(defaultElevation = 4.dp)
    ) {
        Column(
            modifier = Modifier.padding(16.dp),
            horizontalAlignment = Alignment.CenterHorizontally
        ) {
            IconButton(
                onClick = if (isRecording) onStopRecording else onStartRecording,
                modifier = Modifier.size(80.dp)
            ) {
                Icon(
                    imageVector = if (isRecording) Icons.Default.Stop else Icons.Default.Mic,
                    contentDescription = if (isRecording) "停止录音" else "开始录音",
                    modifier = Modifier.size(60.dp),
                    tint = if (isRecording) Color.Red else Color.Blue
                )
            }
            
            Text(
                text = if (isRecording) "正在录音..." else "点击开始录音",
                style = MaterialTheme.typography.bodyLarge
            )
        }
    }
}

6. 性能优化方案

6.1 内存优化

• 使用对象池管理音频缓冲区
• 及时释放Vosk模型资源
• 限制识别结果缓存大小

6.2 CPU优化

• 使用协程处理异步任务
• 音频处理在后台线程执行
• 优化拼音/音标转换算法

6.3 存储优化

• 模型文件压缩存储
• 使用增量更新机制
• 清理临时音频文件

7. 测试方案

7.1 单元测试

• 拼音转换算法测试
• 音标转换算法测试
• 评分算法测试

7.2 集成测试

• Vosk引擎集成测试
• 端到端录音识别测试
• 性能压力测试

7.3 用户体验测试

• 不同口音用户测试
• 不同环境噪音测试
• 界面交互测试

8. 部署方案

8.1 模型部署

• 将Vosk模型打包到APK中
• 支持模型热更新
• 提供模型下载功能

8.2 版本管理

• 语义化版本号
• 向后兼容性保证
• 灰度发布策略

9. 扩展功能

9.1 高级功能

• 发音波形可视化
• 发音历史记录
• 个性化学习计划

9.2 多语言支持

• 支持更多语言模型
• 国际化界面
• CMC多地区发音变体支持（美式、英式、澳式等）
• 基于CMC的发音标准选择

这个技术方案提供了一个完整的Android拼读打分系统设计，涵盖了从语音识别到评分算法的所有核心功能，具有良好的可扩展性和性能优化考虑。