Class atsvb

General configuration options

config = {
   customer_id: 'customer_id', // Specify customer_id (can also be specified by passing it to the SDK constructor)
   api_url: 'url', // Custom URL for SDK authentication, applicable for on-premises
   sdk_url: 'url',  // Specifies the URL to the SDK folder in case you host model files yourself
   preset: 'balanced', / You can specify the default segmentation preset (quality, speed, balanced)
   sample_rate: 48000, // You can specify the default sample rate for model processing
   context_sample_rate: 48000, // Sample rate of the internal AudioContext. 0 (default) lets the browser choose. Set it to match the encoder (e.g. 48000 for Opus) to avoid an extra resampling step on the output track. Must be set before the input stream is attached.
   cacheModels: true, // If true, the SDK will load ML models locally, making subsequent loads faster with no network requests
   processingChunk: 64, // Frame size for communication between worklet and worker in milliseconds; higher value -> more latency and less CPU usage, and vice versa
   latency_mode: 'auto', // Latency policy: 'auto', 'low', or 'stable'. Auto starts low and backs off after underruns.
   denoise_stages: { enabled: true, noiseOnlyLsnrDb: -10, skipDfLsnrDb: 20, bypassLsnrDb: 30 }, // LSNR-based stage skipping for the wasm presets; see setDenoiseStages()
   processorType: 'worklet', // Specify the processor type: 'worklet' for real-time streaming or 'buffer' for file processing
   wasmPaths: { // Currently, WASM files are loaded from the same directory where the SDK is placed, but custom URLs are also supported (e.g., loading from CDNs)
       'ort-wasm.wasm': 'url',
       'ort-wasm-simd.wasm': 'url',
   }
}

Example of how to change default denoise quality preset

config = {
   preset: 'quality'
   sample_rate: 48000
}

Example of how to configure processor type for file processing

config = {
   processorType: 'buffer'  // Use buffer processor for file processing instead of real-time streaming
}

Example of how to hot models on custom domain

config = {
   sdk_url: 'https://domain.com/sdk/'  // in this derectory should be subfolder models with all required models
}

sdk.config({ sdk_url: 'https://cdn.example.com/audio/' });
for (const m of sdk.getRequiredModels()) {
  const res = await fetch(m.url, { method: 'HEAD' });
  if (!res.ok) console.error(`missing model for "${m.preset}": ${m.path}`);
}

export interface ErrorObject {
 message: string;
 type: ErrorType;
 code?: ErrorCode;
 emitter?: ErrorEmitter;
 cause?: Error;
 data?: any;
}

export enum ErrorCode {
 PERFORMANCE_STOP = 1001, // When the SDK can't perform processing in real-time and latency becomes too high, it will stop processing and bypass the original audio to the output to prevent breaking the user experience and causing audio issues.
 REDUCE_LATENCY = 1002, // When we receive more processed frames than we can render at the moment (this may happen due to short-term performance issues or the browser lowering worker priority), the SDK will increase the speed of the voice (from 10% to 20%) to stabilize latency.
 MODEL_LOAD_FAILED = 1010, // Mostly related to network issues during model loading
 PROCESSOR_INIT_ISSUE = 1020, // Issue during initialization of the ML processor
 AUTH_ISSUE = 1030, // Authentication issue
 SUPPORT_ISSUE = 1040, // Balanced model isn't supported without SIMD support
 PROCESSING_PROGRESS = 1060, // Progress of audio buffer processing
}

export enum ErrorType {
 INFO = "info",
 WARNING = "warning",
 ERROR = "error",
}

const sdk = new atsvb('customer_id');
sdk.config({ 
  processorType: 'buffer',
  preset: 'balanced',
  sample_rate: 32000
});

// Process audio buffer
const inputAudio = new Float32Array(32000); // 1 second at 32kHz
const processedAudio = await sdk.processBuffer(inputAudio, 32000);