streaming_asr.js

/**
 * Streaming ASR Demo - JavaScript Implementation with Web Workers
 *
 * Architecture:
 * - Main thread: Audio capture, VAD, UI updates
 * - Encoder Worker: Preprocessor + Encoder ONNX inference
 * - Decoder Worker: Adapter + Decoder ONNX inference
 */

// =============================================================================
// Constants
// =============================================================================

const SAMPLE_RATE = 16000;
const VAD_CHUNK_SAMPLES = 160;  // 10ms - optimal for TenVAD
const ASR_CHUNK_SAMPLES = 320;  // 20ms - Moonshine frame size
const ENCODER_BATCH_SAMPLES = 5120;  // 320ms - batch size for encoder

const PRE_BUFFER_CHUNKS = 15;  // ~300ms at 20ms chunks
const POST_BUFFER_CHUNKS = 3;  // ~60ms at 20ms chunks

const MODEL_CONFIGS = {
    sleeker: {
        dim: 336,
        dec_dim: 288,
        depth: 6,
        encoder_depth: 6,
        n_past: 16,
        n_future: 4,
        nheads: 8,
        head_dim: 36,
        vocab_size: 32768
    },
    spindlier: {
        dim: 620,
        dec_dim: 512,
        depth: 10,
        encoder_depth: 10,
        n_past: 16,
        n_future: 4,
        nheads: 8,
        head_dim: 64,
        vocab_size: 32768
    }
};

// =============================================================================
// TenVAD - WebAssembly-based Voice Activity Detection
// =============================================================================

class TenVAD {
    constructor(hopSize = 160, threshold = 0.5) {
        this.hopSize = hopSize;
        this.threshold = threshold;
        this.module = null;
        this.vadHandle = null;
        this.audioPtr = null;
        this.probPtr = null;
        this.flagPtr = null;
        this.ready = false;
    }

    async init(wasmUrl = './ten_vad.js') {
        const wasmBinaryUrl = wasmUrl.replace('.js', '.wasm');

        // Dynamic import of the ES module
        const vadModule = await import(wasmUrl);
        const createTenVadModule = vadModule.default;

        this.module = await createTenVadModule({
            locateFile: (path) => {
                if (path.endsWith('.wasm')) {
                    return wasmBinaryUrl;
                }
                return path;
            }
        });

        // Create VAD instance
        const vadHandlePtr = this.module._malloc(4);
        const result = this.module._ten_vad_create(vadHandlePtr, this.hopSize, this.threshold);

        if (result !== 0) {
            this.module._free(vadHandlePtr);
            throw new Error(`Failed to create TenVAD instance: ${result}`);
        }

        this.vadHandle = this.module.HEAP32[vadHandlePtr / 4];
        this.module._free(vadHandlePtr);

        // Allocate buffers
        this.audioPtr = this.module._malloc(this.hopSize * 2);
        this.probPtr = this.module._malloc(4);
        this.flagPtr = this.module._malloc(4);

        this.ready = true;
    }

    process(audioChunkFloat32) {
        if (!this.ready) return -1;

        const int16Data = new Int16Array(this.hopSize);
        for (let i = 0; i < this.hopSize && i < audioChunkFloat32.length; i++) {
            int16Data[i] = Math.max(-32768, Math.min(32767, Math.round(audioChunkFloat32[i] * 32767)));
        }

        this.module.HEAP16.set(int16Data, this.audioPtr / 2);
        this.module._ten_vad_process(this.vadHandle, this.audioPtr, this.hopSize, this.probPtr, this.flagPtr);

        return this.module.HEAPF32[this.probPtr / 4];
    }

    destroy() {
        if (!this.ready || !this.module) return;

        this.ready = false;  // Prevent further use

        try {
            if (this.audioPtr) {
                this.module._free(this.audioPtr);
                this.audioPtr = null;
            }
            if (this.probPtr) {
                this.module._free(this.probPtr);
                this.probPtr = null;
            }
            if (this.flagPtr) {
                this.module._free(this.flagPtr);
                this.flagPtr = null;
            }
            // Skip _ten_vad_destroy as it causes memory access errors
            // The WASM memory will be cleaned up when the module is garbage collected
            this.vadHandle = null;
        } catch (e) {
            console.warn('TenVAD cleanup error:', e);
        }

        this.module = null;
    }
}

// Fallback simple energy-based VAD
class SimpleVAD {
    constructor(sampleRate = 16000, frameSize = 160) {
        this.frameSize = frameSize;
        this.energyHistory = [];
        this.historySize = 50;
        this.noiseFloor = 0.001;
        this.ready = true;
    }

    async init() {}

    process(audioChunk) {
        let energy = 0;
        for (let i = 0; i < audioChunk.length; i++) {
            energy += audioChunk[i] * audioChunk[i];
        }
        energy = Math.sqrt(energy / audioChunk.length);

        this.energyHistory.push(energy);
        if (this.energyHistory.length > this.historySize) {
            this.energyHistory.shift();
        }

        if (this.energyHistory.length > 10) {
            const sorted = [...this.energyHistory].sort((a, b) => a - b);
            this.noiseFloor = sorted[Math.floor(sorted.length * 0.1)] || 0.001;
        }

        const snr = energy / (this.noiseFloor + 1e-10);
        return 1 / (1 + Math.exp(-2 * (snr - 3)));
    }

    destroy() {}
}

// =============================================================================
// Pipelined Streaming ASR with Web Workers
// =============================================================================

class PipelinedStreamingASR {
    constructor(config) {
        this.modelName = config.modelName || 'sleeker';
        this.onnxUrl = config.onnxUrl || './models';
        this.onsetThreshold = config.onsetThreshold || 0.5;
        this.offsetThreshold = config.offsetThreshold || 0.3;
        this.emaAlpha = config.emaAlpha || 0.3;

        this.cfg = MODEL_CONFIGS[this.modelName];

        // Workers
        this.encoderWorker = null;
        this.decoderWorker = null;
        this.encoderReady = false;
        this.decoderReady = false;

        // VAD (runs on main thread for low latency)
        this.vad = null;

        // Audio capture
        this.audioContext = null;
        this.sourceNode = null;
        this.workletNode = null;

        // State
        this.running = false;
        this.state = 'idle';
        this.currentSegmentId = 0;
        this.emaProb = 0;
        this.onsetCounter = 0;
        this.offsetCounter = 0;

        // Buffers
        this.vadBuffer = [];
        this.asrBuffer = [];
        this.preBuffer = [];
        this.postBufferRemaining = 0;
        this.encoderBatchBuffer = [];  // Accumulate 320ms before sending to encoder

        // Display state
        this.vadHistory = [];
        this.vadUpdateCounter = 0;
        this.vadUpdateInterval = 5;  // Update display every 5 VAD chunks (50ms)

        // Callbacks
        this.onVadUpdate = null;
        this.onTranscript = null;
        this.onLiveCaption = null;
        this.onStatusUpdate = null;
        this.onQueueUpdate = null;
    }

    async loadModels(progressCallback, detailedProgressCallback) {
        // Track overall progress
        const totalModels = 7;  // VAD, Preprocessor, Encoder, Tokenizer, Adapter, Decoder Init, Decoder Step
        let completedModels = 0;
        let currentModel = '';
        let currentProgress = { loaded: 0, total: 0 };

        const updateProgress = () => {
            const overallPercent = (completedModels / totalModels) * 100;
            detailedProgressCallback?.({
                completedModels,
                totalModels,
                overallPercent,
                currentModel,
                currentProgress
            });
        };

        // Initialize VAD
        try {
            currentModel = 'VAD';
            progressCallback?.('Loading TenVAD...');
            updateProgress();
            this.vad = new TenVAD(VAD_CHUNK_SAMPLES, 0.5);
            await this.vad.init('./ten_vad.js');
            console.log('Using TenVAD');
            completedModels++;
            updateProgress();
        } catch (e) {
            console.warn('TenVAD failed, using SimpleVAD:', e.message);
            this.vad = new SimpleVAD(SAMPLE_RATE, VAD_CHUNK_SAMPLES);
            await this.vad.init();
            completedModels++;
            updateProgress();
        }

        // Initialize Encoder Worker with progress tracking
        progressCallback?.('Loading encoder models...');
        await this.initEncoderWorker((model, progress) => {
            currentModel = model;
            currentProgress = progress;
            updateProgress();
        }, () => {
            completedModels++;
            updateProgress();
        });

        // Initialize Decoder Worker with progress tracking
        progressCallback?.('Loading decoder models...');
        await this.initDecoderWorker((model, progress) => {
            currentModel = model;
            currentProgress = progress;
            updateProgress();
        }, () => {
            completedModels++;
            updateProgress();
        });

        progressCallback?.('Ready!');
    }

    initEncoderWorker(onProgress, onModelDone) {
        return new Promise((resolve, reject) => {
            this.encoderWorker = new Worker('./encoder_worker.js');

            this.encoderWorker.onmessage = (e) => {
                const { type } = e.data;

                switch (type) {
                    case 'ready':
                        this.encoderReady = true;
                        resolve();
                        break;
                    case 'error':
                        reject(new Error(e.data.message));
                        break;
                    case 'status':
                        // Progress update from worker
                        break;
                    case 'progress':
                        onProgress?.(e.data.model, { loaded: e.data.loaded, total: e.data.total });
                        break;
                    case 'model_done':
                        onModelDone?.(e.data.model);
                        break;
                    case 'segment_start':
                        this.decoderWorker?.postMessage({ type: 'segment_start', data: { segmentId: e.data.segmentId } });
                        break;
                    case 'segment_end':
                        this.decoderWorker?.postMessage({ type: 'segment_end', data: { segmentId: e.data.segmentId } });
                        break;
                    case 'features':
                        // Forward features to decoder worker
                        this.decoderWorker?.postMessage({
                            type: 'features',
                            data: {
                                segmentId: e.data.segmentId,
                                features: e.data.features,
                                dims: e.data.dims
                            }
                        }, [e.data.features.buffer]);
                        break;
                }
            };

            this.encoderWorker.postMessage({
                type: 'init',
                data: {
                    cfg: this.cfg,
                    onnxUrl: this.onnxUrl,
                    modelName: this.modelName
                }
            });
        });
    }

    initDecoderWorker(onProgress, onModelDone) {
        return new Promise((resolve, reject) => {
            this.decoderWorker = new Worker('./decoder_worker.js');

            this.decoderWorker.onmessage = (e) => {
                const { type } = e.data;

                switch (type) {
                    case 'ready':
                        this.decoderReady = true;
                        resolve();
                        break;
                    case 'error':
                        reject(new Error(e.data.message));
                        break;
                    case 'status':
                        break;
                    case 'progress':
                        onProgress?.(e.data.model, { loaded: e.data.loaded, total: e.data.total });
                        break;
                    case 'model_done':
                        onModelDone?.(e.data.model);
                        break;
                    case 'transcript':
                        this.onTranscript?.(e.data.text, e.data.segmentId);
                        break;
                    case 'live_caption':
                        this.onLiveCaption?.(e.data.text);
                        break;
                }
            };

            this.decoderWorker.postMessage({
                type: 'init',
                data: {
                    cfg: this.cfg,
                    onnxUrl: this.onnxUrl,
                    modelName: this.modelName
                }
            });
        });
    }

    async start() {
        if (this.running) return;

        const stream = await navigator.mediaDevices.getUserMedia({
            audio: {
                sampleRate: SAMPLE_RATE,
                channelCount: 1,
                echoCancellation: false,
                noiseSuppression: false,
                autoGainControl: false
            }
        });

        this.audioContext = new AudioContext({ sampleRate: SAMPLE_RATE });

        // Check actual sample rate
        console.log(`Requested sample rate: ${SAMPLE_RATE}, Actual: ${this.audioContext.sampleRate}`);
        this.sourceNode = this.audioContext.createMediaStreamSource(stream);

        // Use AudioWorklet for better performance
        try {
            await this.audioContext.audioWorklet.addModule('./audio_processor.js');
            this.workletNode = new AudioWorkletNode(this.audioContext, 'audio-processor');

            this.workletNode.port.onmessage = (e) => {
                if (this.running) {
                    this.processAudioChunk(e.data.audio);
                }
            };

            this.sourceNode.connect(this.workletNode);
            this.workletNode.connect(this.audioContext.destination);
        } catch (e) {
            // Fallback to ScriptProcessor
            console.warn('AudioWorklet not available, using ScriptProcessor');
            const bufferSize = 2048;
            this.scriptNode = this.audioContext.createScriptProcessor(bufferSize, 1, 1);

            this.scriptNode.onaudioprocess = (e) => {
                if (this.running) {
                    const inputData = e.inputBuffer.getChannelData(0);
                    this.processAudioChunk(new Float32Array(inputData));
                }
            };

            this.sourceNode.connect(this.scriptNode);
            this.scriptNode.connect(this.audioContext.destination);
        }

        this.running = true;
        this.state = 'idle';
        this.onsetCounter = 0;
        this.offsetCounter = 0;
        this.emaProb = 0;

        this.onStatusUpdate?.('listening', 'Listening...');
    }

    stop() {
        this.running = false;

        if (this.workletNode) {
            this.workletNode.disconnect();
            this.workletNode = null;
        }
        if (this.scriptNode) {
            this.scriptNode.disconnect();
            this.scriptNode = null;
        }
        if (this.sourceNode) {
            this.sourceNode.disconnect();
            this.sourceNode = null;
        }
        if (this.audioContext) {
            this.audioContext.close();
            this.audioContext = null;
        }
        if (this.vad) {
            this.vad.destroy();
        }
        if (this.encoderWorker) {
            this.encoderWorker.terminate();
            this.encoderWorker = null;
        }
        if (this.decoderWorker) {
            this.decoderWorker.terminate();
            this.decoderWorker = null;
        }

        this.onStatusUpdate?.('idle', 'Stopped');
    }

    processAudioChunk(audioData) {
        // Accumulate for VAD (10ms chunks)
        this.vadBuffer.push(...audioData);

        // Accumulate for ASR (20ms chunks)
        this.asrBuffer.push(...audioData);

        // Process VAD chunks
        while (this.vadBuffer.length >= VAD_CHUNK_SAMPLES) {
            const vadChunk = new Float32Array(this.vadBuffer.splice(0, VAD_CHUNK_SAMPLES));
            const prob = this.vad.process(vadChunk);

            if (prob >= 0) {
                this.emaProb = this.emaAlpha * prob + (1 - this.emaAlpha) * this.emaProb;

                // Throttle display updates (every 50ms instead of 10ms)
                this.vadUpdateCounter++;
                if (this.vadUpdateCounter >= this.vadUpdateInterval) {
                    this.vadUpdateCounter = 0;
                    this.vadHistory.push(this.emaProb);
                    if (this.vadHistory.length > 100) this.vadHistory.shift();
                    this.onVadUpdate?.(this.emaProb, this.vadHistory);
                }

                this.updateSegmentState();
            }
        }

        // Extract complete ASR chunks
        while (this.asrBuffer.length >= ASR_CHUNK_SAMPLES) {
            const chunkData = this.asrBuffer.splice(0, ASR_CHUNK_SAMPLES);
            const chunk = new Float32Array(chunkData);

            if (this.state === 'speech') {
                this.sendAudioToEncoder(chunk);
            } else {
                this.preBuffer.push(chunk);
                if (this.preBuffer.length > PRE_BUFFER_CHUNKS) {
                    this.preBuffer.shift();
                }

                if (this.postBufferRemaining > 0) {
                    this.sendAudioToEncoder(chunk);
                    this.postBufferRemaining--;

                    if (this.postBufferRemaining === 0) {
                        this.finalizeSegmentEnd();
                    }
                }
            }
        }
    }

    sendAudioToEncoder(chunk, flush = false) {
        if (!this.encoderWorker || !this.encoderReady) return;

        // Accumulate chunks into batch buffer
        this.encoderBatchBuffer.push(...chunk);

        // Send when we have 320ms worth of audio, or on flush
        if (this.encoderBatchBuffer.length >= ENCODER_BATCH_SAMPLES || flush) {
            if (this.encoderBatchBuffer.length > 0) {
                const batch = new Float32Array(this.encoderBatchBuffer);
                this.encoderBatchBuffer = [];

                this.encoderWorker.postMessage({
                    type: 'audio',
                    data: {
                        audio: batch,
                        segmentId: this.currentSegmentId
                    }
                }, [batch.buffer]);
            }
        }
    }

    updateSegmentState() {
        if (this.state === 'idle') {
            if (this.emaProb >= this.onsetThreshold) {
                this.onsetCounter++;
                if (this.onsetCounter >= 2) {
                    this.startSegment();
                }
            } else {
                this.onsetCounter = 0;
            }
        } else if (this.state === 'speech') {
            if (this.emaProb < this.offsetThreshold) {
                this.offsetCounter++;
                if (this.offsetCounter >= 3) {
                    this.endSegment();
                }
            } else {
                this.offsetCounter = 0;
            }
        }
    }

    startSegment() {
        this.currentSegmentId++;
        this.state = 'speech';
        this.onsetCounter = 0;
        this.offsetCounter = 0;
        this.encoderBatchBuffer = [];  // Reset batch buffer for new segment

        // Tell encoder to start new segment
        this.encoderWorker?.postMessage({
            type: 'segment_start',
            data: { segmentId: this.currentSegmentId }
        });

        // Drain pre-buffer
        while (this.preBuffer.length > 0) {
            const chunk = this.preBuffer.shift();
            this.sendAudioToEncoder(chunk);
        }

        this.onStatusUpdate?.('recording', 'Recording...');
    }

    endSegment() {
        this.state = 'idle';
        this.offsetCounter = 0;
        this.postBufferRemaining = POST_BUFFER_CHUNKS;

        if (this.postBufferRemaining === 0) {
            this.finalizeSegmentEnd();
        }

        this.onStatusUpdate?.('listening', 'Listening...');
    }

    finalizeSegmentEnd() {
        // Process remaining complete chunks
        while (this.asrBuffer.length >= ASR_CHUNK_SAMPLES) {
            const chunkData = this.asrBuffer.splice(0, ASR_CHUNK_SAMPLES);
            const chunk = new Float32Array(chunkData);
            this.sendAudioToEncoder(chunk);
        }

        // Pad and send partial chunk
        if (this.asrBuffer.length > 0) {
            const padded = new Float32Array(ASR_CHUNK_SAMPLES);
            padded.set(this.asrBuffer);
            this.sendAudioToEncoder(padded);
        }
        this.asrBuffer = [];

        // Flush any remaining audio in the batch buffer
        this.sendAudioToEncoder(new Float32Array(0), true);

        // Signal segment end
        this.encoderWorker?.postMessage({
            type: 'segment_end',
            data: { segmentId: this.currentSegmentId }
        });
    }
}

// =============================================================================
// UI Controller
// =============================================================================

class ASRDemoUI {
    constructor() {
        this.asr = null;
        this.vadCanvas = null;
        this.vadCtx = null;

        this.initElements();
        this.initCanvas();
        this.bindEvents();
    }

    initElements() {
        this.loadingOverlay = document.getElementById('loadingOverlay');
        this.loadingText = document.getElementById('loadingText');
        this.loadingProgressFill = document.getElementById('loadingProgressFill');
        this.loadingProgressText = document.getElementById('loadingProgressText');
        this.loadingDetails = document.getElementById('loadingDetails');
        this.errorMessage = document.getElementById('errorMessage');
        this.statusDot = document.getElementById('statusDot');
        this.statusText = document.getElementById('statusText');
        this.startBtn = document.getElementById('startBtn');
        this.stopBtn = document.getElementById('stopBtn');
        this.vadBarFill = document.getElementById('vadBarFill');
        this.vadValue = document.getElementById('vadValue');
        this.audioQueueSize = document.getElementById('audioQueueSize');
        this.featuresQueueSize = document.getElementById('featuresQueueSize');
        this.droppedChunksEl = document.getElementById('droppedChunks');
        this.transcriptsList = document.getElementById('transcriptsList');
        this.liveCaption = document.getElementById('liveCaption');
        this.liveCaptionText = document.getElementById('liveCaptionText');
        this.modelSelect = document.getElementById('modelSelect');
        this.onnxUrl = document.getElementById('onnxUrl');
        this.onsetThreshold = document.getElementById('onsetThreshold');
        this.offsetThreshold = document.getElementById('offsetThreshold');
    }

    initCanvas() {
        this.vadCanvas = document.getElementById('vadCanvas');
        this.vadCtx = this.vadCanvas.getContext('2d');

        const rect = this.vadCanvas.getBoundingClientRect();
        this.vadCanvas.width = rect.width * window.devicePixelRatio;
        this.vadCanvas.height = rect.height * window.devicePixelRatio;
        this.vadCtx.scale(window.devicePixelRatio, window.devicePixelRatio);
    }

    bindEvents() {
        this.startBtn.addEventListener('click', () => this.handleStart());
        this.stopBtn.addEventListener('click', () => this.handleStop());
    }

    async handleStart() {
        try {
            this.showLoading('Initializing...');

            const config = {
                modelName: this.modelSelect.value,
                onnxUrl: this.onnxUrl.value || './models',
                onsetThreshold: parseFloat(this.onsetThreshold.value),
                offsetThreshold: parseFloat(this.offsetThreshold.value)
            };

            this.asr = new PipelinedStreamingASR(config);

            this.asr.onVadUpdate = (prob, history) => this.updateVadDisplay(prob, history);
            this.asr.onTranscript = (text, segmentId) => this.addTranscript(text, segmentId);
            this.asr.onLiveCaption = (text) => this.updateLiveCaption(text);
            this.asr.onStatusUpdate = (status, text) => this.updateStatus(status, text);

            await this.asr.loadModels(
                (text) => {
                    this.loadingText.textContent = text;
                },
                (progress) => {
                    this.updateLoadingProgress(progress);
                }
            );

            await this.asr.start();

            this.hideLoading();
            this.startBtn.disabled = true;
            this.stopBtn.disabled = false;
            this.disableConfig(true);

        } catch (error) {
            console.error('Start error:', error);
            this.hideLoading();
            this.showError(`Failed to start: ${error.message}`);
        }
    }

    handleStop() {
        if (this.asr) {
            this.asr.stop();
            this.asr = null;
        }

        this.startBtn.disabled = false;
        this.stopBtn.disabled = true;
        this.disableConfig(false);
        this.updateStatus('idle', 'Ready');
    }

    updateVadDisplay(prob, history) {
        this.vadBarFill.style.width = `${prob * 100}%`;
        this.vadValue.textContent = `${Math.round(prob * 100)}%`;

        const ctx = this.vadCtx;
        const rect = this.vadCanvas.getBoundingClientRect();
        const width = rect.width;
        const height = rect.height;

        ctx.fillStyle = '#0f0f23';
        ctx.fillRect(0, 0, width, height);

        if (history.length < 2) return;

        const onsetY = height * (1 - parseFloat(this.onsetThreshold.value));
        const offsetY = height * (1 - parseFloat(this.offsetThreshold.value));

        ctx.strokeStyle = '#ff444466';
        ctx.beginPath();
        ctx.moveTo(0, onsetY);
        ctx.lineTo(width, onsetY);
        ctx.stroke();

        ctx.strokeStyle = '#00ff8866';
        ctx.beginPath();
        ctx.moveTo(0, offsetY);
        ctx.lineTo(width, offsetY);
        ctx.stroke();

        ctx.strokeStyle = '#00d4ff';
        ctx.lineWidth = 2;
        ctx.beginPath();

        for (let i = 0; i < history.length; i++) {
            const x = (i / (history.length - 1)) * width;
            const y = height * (1 - history[i]);
            if (i === 0) {
                ctx.moveTo(x, y);
            } else {
                ctx.lineTo(x, y);
            }
        }
        ctx.stroke();
    }

    addTranscript(text, segmentId) {
        if (!text || !text.trim()) return;

        const item = document.createElement('div');
        item.className = 'transcript-item';
        item.innerHTML = `
            <span class="transcript-duration">#${segmentId}</span>
            <span class="transcript-text">${this.escapeHtml(text)}</span>
        `;
        this.transcriptsList.appendChild(item);
        this.transcriptsList.scrollTop = this.transcriptsList.scrollHeight;
    }

    updateLiveCaption(text) {
        if (text) {
            this.liveCaptionText.textContent = text;
            this.liveCaptionText.classList.remove('placeholder');
            this.liveCaption.classList.add('active');
        } else {
            this.liveCaptionText.textContent = 'Waiting for speech...';
            this.liveCaptionText.classList.add('placeholder');
            this.liveCaption.classList.remove('active');
        }
    }

    updateStatus(status, text) {
        this.statusDot.className = 'status-dot ' + status;
        this.statusText.textContent = text;
    }

    showLoading(text) {
        this.loadingText.textContent = text;
        this.loadingProgressFill.style.width = '0%';
        this.loadingProgressText.textContent = '0 / 7 models';
        this.loadingDetails.textContent = '';
        this.loadingOverlay.classList.remove('hidden');
    }

    hideLoading() {
        this.loadingOverlay.classList.add('hidden');
    }

    updateLoadingProgress(progress) {
        const { completedModels, totalModels, currentModel, currentProgress } = progress;

        // Update overall progress bar
        const overallPercent = (completedModels / totalModels) * 100;
        this.loadingProgressFill.style.width = `${overallPercent}%`;
        this.loadingProgressText.textContent = `${completedModels} / ${totalModels} models`;

        // Update details with current model and byte progress
        if (currentModel && currentProgress.total > 0) {
            const loadedMB = (currentProgress.loaded / (1024 * 1024)).toFixed(1);
            const totalMB = (currentProgress.total / (1024 * 1024)).toFixed(1);
            const percent = Math.round((currentProgress.loaded / currentProgress.total) * 100);
            this.loadingDetails.textContent = `${currentModel}: ${loadedMB} / ${totalMB} MB (${percent}%)`;
        } else if (currentModel) {
            this.loadingDetails.textContent = `Loading ${currentModel}...`;
        }
    }

    showError(message) {
        this.errorMessage.textContent = message;
        this.errorMessage.classList.add('visible');
    }

    disableConfig(disabled) {
        this.modelSelect.disabled = disabled;
        this.onnxUrl.disabled = disabled;
        this.onsetThreshold.disabled = disabled;
        this.offsetThreshold.disabled = disabled;
    }

    escapeHtml(text) {
        const div = document.createElement('div');
        div.textContent = text;
        return div.innerHTML;
    }
}

// Initialize on page load
document.addEventListener('DOMContentLoaded', () => {
    window.asrDemo = new ASRDemoUI();
});