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AUDIO & SPEECH
Audio & Speech Data Services
Transcription, speaker diarization, intent detection, sentiment analysis, phonetic labeling, and sound event detection — with millisecond-level timestamp precision, native-speaker annotators across 20+ languages, and measurable WER/DER quality benchmarks.
Hours Transcribed
Clean Audio Accuracy
Languages
Diarization Accuracy
Timestamp Precision
Dialect Variants
Capabilities
Six Core Audio & Speech Services
Verbatim & Clean-Read Transcription
Verbatim transcription preserving disfluencies, false starts, filler words, and overlapping speech — or clean-read transcription with normalized text. Word-level timestamps, speaker attribution, and domain-specific vocabulary handling for medical, legal, and technical audio.
Speaker Diarization & Attribution
Accurate speaker segmentation, identity labeling, and turn-taking annotation in multi-party conversations, meetings, interviews, call center recordings, and podcast/broadcast content. Support for overlapping speech detection, speaker change points, and cross-session speaker linking.
Intent Classification & Slot Filling
Intent classification and slot/entity extraction at the utterance level for training voice assistants, IVR systems, chatbots, and conversational AI. Custom intent taxonomies with hierarchical structure, slot types with value normalization, and multi-intent support for complex utterances.
Sentiment, Emotion & Tone Analysis
Sentiment polarity, discrete emotion classification (Ekman 6 + neutral, or custom taxonomy), arousal/valence scoring, tone analysis, and sarcasm/irony detection — all time-aligned to specific utterances or segments within the audio. Powers customer experience analytics, media monitoring, and empathetic AI.
Multilingual & Accent-Aware Annotation
Transcription, diarization, and classification across 20+ languages — each with native-speaker annotators who understand dialect variations, code-switching patterns, and cultural context. Accent-aware annotation captures speaker characteristics for accent-robust ASR training.
Sound Event Detection & Phonetic Labeling
Non-speech audio classification (environmental sounds, music, alerts), phonetic transcription (IPA), prosody annotation (stress, intonation, rhythm), and pronunciation assessment for TTS training, voice cloning, and accessibility applications.
Voice Assistants & Smart Speakers
Wake word detection, command recognition, multi-turn conversation, and multi-language support training data. Custom intent/entity schemas for your product's domain.
Call Center Analytics
Customer interaction analysis — sentiment tracking, agent quality scoring, topic classification, call summarization, and compliance monitoring training data.
Medical Transcription
Clinical conversation transcription with medical terminology, procedure codes, and HIPAA-compliant workflows. De-identified transcripts for clinical NLP model training.
Media, Podcasts & Accessibility
Content transcription, speaker identification, topic segmentation, subtitle generation, and audio description for media companies and accessibility compliance.
Word Error Rate (WER) Tracking
WER measured against expert-transcribed gold standards per batch. Targets: ≤ 3% for clean studio audio, ≤ 5% for conversational, ≤ 8% for noisy or accented. Batches exceeding thresholds are rejected and re-transcribed.
Timestamp Validation
Automated validation of word-level and utterance-level timestamps against audio waveforms. Checks for gaps, overlaps, out-of-order timestamps, and alignment drift. Critical for subtitle generation and time-aligned analytics.
Speaker Boundary Validation
Automated checks for speaker turn boundaries — no overlapping speaker labels (unless annotated overlap), consistent speaker IDs, and no orphaned segments. Cross-referenced against diarization confidence scores.
Domain Vocabulary Accuracy
Custom dictionaries for medical, legal, financial, and technical terminology. Annotators tested on domain-specific gold sets before production. Vocabulary updates distributed within 24 hours of approval. Unknown terms flagged for dictionary expansion.
Inter-Transcriber Agreement
Double-transcription of 10% random sample per batch. Character-level and word-level agreement measured. Disagreements trigger review and recalibration. Persistent disagreement patterns identified for guideline updates.
Accent & Dialect Quality Assurance
Transcribers matched to speaker accent/dialect. Accent-specific gold sets validate regional vocabulary, pronunciation variants, and code-switching patterns. Mismatched assignments flagged and reassigned.
Comparison
UTL Audio Services vs. Typical Providers
| Capability | UTL Data Engine | Typical Provider |
|---|---|---|
| WER tracking per batch with rejection thresholds | ✓ | Aggregate WER only |
| Word-level timestamps (±50ms accuracy) | ✓ | Utterance-level only |
| Speaker overlap detection and annotation | ✓ | |
| 20+ languages with native-speaker transcribers | ✓ | 10–12 languages |
| Accent/dialect matching to transcribers | ✓ | Generic assignment |
| Code-switching annotation (per-word language tags) | ✓ | |
| Sound event detection (100+ categories) | ✓ | Basic noise tags |
| IPA phonetic transcription | ✓ | |
| Emotion trajectory tracking per conversation | ✓ | Overall sentiment only |
| HIPAA-compliant medical transcription | ✓ | Basic redaction |
““UTL handled 50K+ hours of multilingual transcription for our voice assistant across 8 languages. Their native-speaker teams delivered WER ≤ 2.8% on clean audio with word-level timestamps. The accent-matched transcriber assignment and domain-specific medical vocabulary support were exactly what we needed.””
Product Manager
Enterprise Conversational AI Platform
FAQs
Audio & Speech Questions
What audio quality levels can you handle?
We handle everything from studio-quality recordings (WER target ≤ 3%) to noisy call center audio (WER target ≤ 8%). Our QA pipeline adjusts thresholds based on audio quality assessment. For extremely noisy audio, we provide confidence-scored transcriptions with low-confidence segments flagged for client review.
How do you handle accented and dialectal speech?
We match transcribers to the speaker's accent/dialect — not generic 'English' transcribers for Indian English, for example. We maintain accent-specific gold sets and quality benchmarks. For 50+ dialect variants across our supported languages, we have pre-qualified accent-matched teams.
Can you handle overlapping speech in meetings?
Yes. Our diarization annotation includes overlap detection and attribution. When two or more speakers talk simultaneously, we annotate the overlapping segment with all contributing speaker IDs. Overlap recall ≥ 90% on our benchmark. This is critical for meeting transcription and multi-party conversation analysis.
What file formats do you accept and deliver?
Input: WAV, MP3, FLAC, M4A, OGG, WMA, AIFF, and video files (we extract the audio track). Output: CTM (time-marked), TextGrid (Praat), ELAN, WebVTT, SRT, RTTM (diarization), JSON with timestamps, or your custom schema. We match your pipeline's requirements exactly.
Do you support IPA phonetic transcription?
Yes. Our phonetic annotation team produces International Phonetic Alphabet (IPA) transcriptions at the phone level with ≥ 95% accuracy. We also provide prosody annotation (stress, intonation, rhythm) for TTS training and pronunciation assessment for language learning applications.
How quickly can you scale for a large project?
Scoping + guideline design: 3–5 days. Team assembly + calibration: 5–7 days. Pilot (1K–5K samples): 5–10 days. First labeled batch by Day 20. Full production velocity by Day 25. We maintain pre-qualified teams across major domains for faster ramp-up.
Need Audio & Speech Data?
Let's scope your transcription, diarization, or conversational AI data pipeline — we'll design a pilot within 48 hours.