AI Data Operations
From speech transcription and speaker identification to emotion recognition and sound event detection, our trained domain expert annotators turn raw audio into the model-ready data that speech, sound and language models need.
Capabilities
All audio annotation services that your AI/ML Models need.
CAPABILITY / 01
We convert spoken audio into accurate, time-stamped text, handling multiple languages, accents, overlapping speech, and background noise. Our transcription workflow supports both verbatim and clean-read formats depending on what your model requires.
We label who is speaking and when, across single-speaker and multi-speaker recordings. This includes speaker diarization for calls, meetings, and interviews where distinguishing between voices accurately is essential to AI model performance.
We categorize audio clips by type, context, or content, whether that means sorting by genre, environment, device, or use case.
We tag the sentiment expressed in spoken audio as positive, negative, or neutral, so AI models can learn to detect intent and satisfaction accurately.
We identify and label emotional states in audio, such as happiness, sadness, frustration, urgency, calm, or distress, or any others as per your AI model's requirements.
We tag specific sound events within a recording, footsteps, glass breaking, alarms, machinery, applause, and more, and classify them by type. This supports use cases where the model needs to detect an event, not just transcribe speech.
We annotate the linguistic structure of speech, including language identification, code-switching between languages, dialect variation, and pronunciation markers, giving natural language and speech models the grounding they need to generalize across real-world speakers.
We annotate audio and video together, synchronizing speech, sound, and visual context for AI/ML models that need to understand both channels at once, such as lip-sync detection, multimedia content moderation, or audio-visual sentiment analysis.
We label the acoustic properties of audio itself and background noise conditions, like busy and quiet, supporting AI model training for acoustic scene analysis and audio quality assessment applications.
HAVE A SPECIFIC REQUIREMENT?
Tell us what your model needs. We’ll help you scope the annotation capabilities that fit your project.
Backed by deep domain expertise across 20+ industry verticals, we collect and annotate data your models can rely on.
We audit, correct and validate auto-annotated aerial data against your guidelines before it reaches your training pipeline.
Whether you need precisely annotated training data, real-world data collection, a dedicated in-house team, or other staffing solutions, Qualitas Global delivers all three under one roof. Backed by over a decade of experience, we back every engagement with a risk-free 2-day pilot before you commit.
