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Speech & Audio Data Collection

Voice and audio datasets that reflect real-world speakers, environments, and use cases

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Overview

Speech & Audio Data Collection, treated as an engineered data discipline.

Each program is structured around clear collection requirements, contributor criteria, consent standards, recording guidelines, metadata needs, and audio validation. Programs are delivered through whichever workflow environment best fits the client — inside Argos Myriad, inside client systems, or via secure file exchange.

Use cases

Where Speech & Audio Data Collection is applied.

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Collecting speech data for automatic speech recognition (ASR) systems
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Building voice datasets across accents, dialects, languages, and speaker profiles
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Capturing audio in real-world environments, devices, and acoustic conditions
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Supporting voice assistants, call center AI, accessibility tools, and conversational AI
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Collecting scripted, spontaneous, prompted, or scenario-based speech data
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Preparing audio datasets for transcription, annotation, evaluation, and benchmarking
Why Argos

Why Speech & Audio Data Collection delivers in production.

The challenge

Speech AI systems must perform in the conditions where people actually use them: different accents, speech patterns, background noise, devices, languages, and conversational contexts. When audio data is too narrow, overly scripted, or poorly validated, models struggle with recognition accuracy, fairness, and reliability in production.

Our approach

Argos Data brings global multilingual reach, a vetted contributor network, and quality governance built specifically for speech work. We define speaker profiles, locale requirements, recording environments, prompt design, audio specifications, and metadata standards before collection begins. Datasets are designed to reflect the model's intended users and operating conditions, not just acoustic cleanliness.

What sets us apart

For enterprise AI teams, this connects collection directly to production performance, supporting voice systems that work across the accents, environments, and languages where they will actually be deployed.

Outcome

Outcomes that move from pilot to production.

Speech & Audio Data Collection helps enterprise AI teams build voice and audio datasets that reflect real-world speech behavior and deployment conditions. The result is improved ASR accuracy, better multilingual and accent coverage, stronger voice AI reliability, and a more dependable foundation for production speech systems.