ALPANDIA
Voice AI

Voice Transcription

Enterprise-grade speech-to-text built specifically for the acoustic challenges of telephone and contact center audio — background noise, codec artifacts, accent variation, and simultaneous speech.

Also known asvoice transcription APIspeech to text enterprisecall transcription AIPII redaction transcriptioncontact center transcription

99.2% WER avg

Accuracy

25+ categories

PII Types

60+

Languages

< 200ms

Latency (streaming)

WAV, MP3, OGG, G.711, G.729

Audio Formats

JSON, SRT, VTT, TXT

Output

Capabilities

99.2% Accuracy

Industry-leading accuracy maintained even in noisy call center environments with multiple codec types.

Automatic PII Redaction

Real-time detection and redaction of credit card numbers, SSNs, dates of birth, and other sensitive data.

Custom Entity Recognition

Identify and tag domain-specific entities: product names, account numbers, medical codes, or any custom taxonomy.

Streaming + Batch Modes

Choose streaming for real-time use cases or batch for post-call analytics and archival.

Multi-Speaker Support

Simultaneous transcription of multiple speakers with speaker labeling and timestamp precision.

Confidence Filtering

Per-word and per-segment confidence scores for downstream quality control.

Quick Start

example.ts
const transcript = await alpandia.voice.transcribe({
  audio: audioBuffer,
  language: 'en-US',
  options: {
    piiRedaction: true,
    speakerDiarization: true,
    customVocabulary: ['ALPANDIA', 'SIP', 'AHT'],
  }
});

console.log(transcript.text);       // Full transcript
console.log(transcript.speakers);   // Per-speaker segments
console.log(transcript.redactions); // PII entities found

Use Cases

Quality Assurance

Transcribe 100% of calls for AI-powered QA scoring and compliance review.

Call Analytics

Extract topics, keywords, and business intelligence from every conversation.

Agent Training

Build transcription-based training datasets and coaching materials.

Legal & Compliance

Court-admissible transcripts with speaker labels and timestamp metadata.

Start Using Voice Transcription