Speech Data Collection Services for AI Training

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We design and execute speech data collection programs that give your voice AI the linguistic diversity, acoustic range, and natural variation it needs to work for real people in real conditions. From scripted prompt recording to spontaneous conversational capture — across languages, accents, ages, and environments — we deliver speech datasets built for production-grade ASR, TTS, and voice understanding systems.

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25+ crowdsourcing platforms
30+ industries

Our Expertise

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Read speech

Participants read scripted sentences, word lists, phonetically balanced prompts, and domain-specific phrases aloud. Ideal for ASR and TTS bootstrapping.

Industry use cases

  • automatic speech recognition training
  • text-to-speech voice cloning
  • pronunciation dictionaries
  • phoneme-level acoustic models
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Command & wake word speech

Short utterances, trigger phrases, device commands, and keyword sets recorded across noise levels, distances, and speaker demographics.

Industry use cases

  • voice assistants
  • smart speakers
  • in-car voice control
  • IoT device activation
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Spontaneous & conversational speech

Unscripted dialogues, task-based conversations, interviews, and free-form monologues that reflect natural prosody, hesitation, and disfluency.

Industry use cases

  • conversational AI
  • dialogue systems
  • meeting transcription
  • customer service automation
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Multilingual speech

Scripted and conversational recordings in any target language, including low-resource languages, with native speaker verification and linguistic review.

Industry use cases

  • multilingual ASR engines
  • cross-lingual voice models
  • language identification systems
  • localization of voice products
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Emotional & expressive speech

Acted and elicited recordings covering a defined range of emotional states: neutral, happy, angry, sad, surprised — validated by expert raters.

Industry use cases

  • sentiment analysis from voice
  • mental health monitoring
  • empathetic AI
  • call center affect detection
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Accented & dialectal speech

Region-specific recordings from native and non-native speakers across language variants, dialects, and sociolects — with metadata on speaker origin and background.

Industry use cases

  • accent-robust ASR
  • inclusive voice product development
  • language learning platforms
  • global voice assistant rollout
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Children's speech

Age-stratified recordings from pediatric participants collected under strict parental consent and child data protection protocols.

Industry use cases

  • educational AI
  • pediatric voice assistants
  • child-directed speech synthesis
  • language development tools
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Speech Data Collection Methods

Managed recording sessions

Participants complete guided recording tasks via a web or mobile platform, with real-time audio quality monitoring and re-recording prompts for rejected takes.

In-person & studio sessions

Controlled booth recordings for TTS voice talent, emotional speech, and high-fidelity acoustic models requiring studio-grade quality.

Telephone & VoIP capture

Speech collected over phone channels to simulate real-world acoustic degradation for telephony ASR and call center models

Naturalistic observation

Consented ambient recording in everyday settings — home, office, vehicle — to capture speech in authentic noise conditions.

Synthetic speech augmentation

Existing speech data is extended with pitch, speed, noise, and room response variations to broaden acoustic coverage without additional recording.

Platforms and Tools

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Recording platforms

Proprietary browser-based and mobile recording app, Vocaroo integration, custom telephony capture infrastructure
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Annotation & transcription

Kaldi alignment tools, WebAnno, Label Studio, Prodigy; in-house transcription teams for low-resource languages
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Quality analysis

WebRTC VAD, Py-webrtcvad, MOS estimation tools, SNR and clipping detection pipelines
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Augmentation

Audiomentations, SoX, WavAugment
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Storage & delivery

FLAC and WAV (primary), MP3 and Opus on request; TextGrid, JSON, and CTM formats for aligned transcripts

Project Steps

01 Discovery & requirements scoping
We define language targets, speaker demographics, recording environment, utterance types, volume, and annotation depth. Legal and ethical requirements — including child data protection where applicable — are scoped from day one.
02 Speaker recruitment & demographic planning
We recruit participants matching your demographic specifications — language, age, gender, accent, region — from our global contributor network or via targeted recruitment campaigns.
03 Pilot recording & review
A pilot batch is completed, transcribed, and validated against quality benchmarks before full-scale collection begins. Annotation guidelines are refined based on pilot findings.
04 Full-scale recording & transcription
Recording tasks are distributed to contributors at scale. Transcription, forced alignment, and annotation run in parallel, with daily quality monitoring throughout.
05 Quality assurance
Every file undergoes automated signal quality checks and human transcript review. Inter-annotator agreement is measured and corrective review cycles are applied to any flagged segments.
06 Delivery & suppor
Datasets are delivered in your target format with full metadata — speaker ID, language, recording environment, emotion label, and demographic tags. Iterative top-up batches and model-informed data gap filling are available on an ongoing basis.

Frequently Asked Questions

Do you provide validation and verification for speech data?
Yes. Validation criteria are based on the project's technical specification and can cover file completeness, audio quality, file integrity, metadata, recording conditions, transcription accuracy, speaker requirements, task compliance, and segmentation. Where speech is synchronized with other data, timing and alignment can also be checked. Quality checks take place during collection and again before delivery, with acceptance thresholds and rework procedures agreed in advance. Recordings that fail the requirements can be corrected, re-recorded, or excluded to maintain high-quality datasets for model training.
Can you provide annotation services for collected speech data?
Yes. Speech collection, validation, transcription, and annotation can be handled as a connected workflow, keeping the technical requirements and metadata structure consistent throughout the process. Our 1,100+ labelers and specialists can support speech and audio annotation tasks such as transcription, speaker identification, segmentation, language labeling, sentiment, and other task-specific labels. Annotation guidelines and quality checks are defined according to the requirements of the task.
How do you manage consent, privacy, and speech data usage rights?
Before a collection project starts, we define the applicable lawful basis or source authorization, participant notices and consent requirements, permitted uses, retention period, and data-transfer conditions. Personal information is minimized and can be pseudonymized or anonymized where appropriate. For speech collections, requirements may also cover voice data, speaker metadata, transcripts, and information contained within conversations or recordings. The specific safeguards depend on the type of speech data, the regions involved, and how the client intends to use the resulting dataset for AI, language processing, or recognition models.
Can you collect data in different languages and regions?
Yes. We support multilingual speech data collection covering different languages, dialects, accents, and geographic regions, subject to speaker availability and applicable legal requirements. The project specification can define language quotas, speaker profiles, demographic targets, recording environments, devices, and reviewer qualifications. Native or appropriately qualified speakers and reviewers can be involved when language expertise is required.
How do you maintain speech and audio quality during collection?`
Quality is managed before, during, and after the speech data collection process. Before production, we validate the specification and pilot; during collection, we monitor audio quality, recording conditions, task completion, speaker and language quotas, metadata, and other technical requirements. Automated checks and human review can be applied to identify incomplete recordings, excessive noise, technical problems, or inconsistent data. Speech samples that fail the agreed acceptance criteria can be corrected, re-recorded, or excluded according to predefined rework rules.
How long does a data collection project take?
The timeline depends on the amount of speech data required, number of speakers and languages, recruitment needs, geographic coverage, recording environment, equipment, transcription and annotation requirements, validation procedures, and client review cycles. After assessing feasibility, we provide a project plan covering the pilot, speaker recruitment, production ramp-up, expected collection capacity, quality checks, transcription or annotation stages, and final delivery.

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