Voice and Conversation Data We Collect
Voice AI must understand how people actually speak, not just how sentences appear in text. Stepes designs multilingual speech data collection programs around your specific AI objectives, from tightly controlled scripted recordings to spontaneous conversations in realistic acoustic environments.
Scripted & Read Speech
Collect controlled voice recordings from predefined prompts, phrases, sentences, commands, pronunciation lists, or customer-provided scripts.
Scripted speech provides consistent coverage of specific words, phonemes, sentence structures, terminology, and interaction patterns for ASR, speech synthesis, pronunciation modeling, voice interfaces, and other applications. Stepes can work with your existing scripts or help prepare multilingual recording content for each target market.
Spontaneous & Natural Speech
Capture unscripted speech that reflects the way people naturally communicate through free-form responses, topic discussions, scenario completion, and other controlled spontaneous tasks.
These recordings capture natural hesitations, pauses, phrasing variation, colloquial language, and speaking pace that scripted prompts alone cannot reproduce.
Multi-Speaker Conversations
Build conversational audio datasets from two-person or multi-party interactions, including structured and semi-structured scenarios.
Projects can capture natural turn-taking, interruptions, contextual references, overlapping speech where required, and other characteristics of real conversations.
Commands, Wake Words & Short Utterances
Collect wake words, trigger phrases, voice commands, search queries, navigation requests, smart-device interactions, automotive commands, and other short task-oriented utterances.
Programs can be configured across different speakers, accents, devices, microphone types, distances, and acoustic environments.
Accent, Dialect & Code-Switched Speech
Recruit speakers according to regional accent, dialect, locale, and other project-defined linguistic criteria.
Stepes also supports code-switched datasets in which speakers naturally move between two or more languages within the same utterance or conversation.
Scenario & Domain-Specific Conversations
Create speech datasets around the situations your AI system is designed to handle, including customer support, healthcare, financial services, automotive, travel, retail, technology, and enterprise applications.
Projects can incorporate customer-defined terminology, tasks, conversational goals, and interaction patterns.
Build the Voice Dataset Your Model Actually Needs
Language is only one dimension of effective speech data. Stepes helps define collection variables around your model, users, deployment environment, and intended use case so the resulting dataset reflects the speech conditions your AI is likely to encounter.
Language & Locale
Collect speech for specific languages, countries, and regional variants rather than treating each language as a single uniform population.
Accent & Dialect
Target regional accents, local dialects, pronunciation patterns, and other linguistic variations required by your application.
Speaker Profile
Define project-relevant, approved speaker criteria such as language background, locale, age range, domain experience, or other attributes needed for the dataset.
Device & Microphone
Capture voice through smartphones, laptops, headsets, smart devices, automotive systems, proprietary hardware, or other specified configurations.
Recording Environment
Collect audio in controlled environments or under real-world conditions such as homes, offices, vehicles, public spaces, or other customer-defined settings.
Acoustic Conditions
Design datasets around background noise, microphone distance, reverberation, speaker position, and environmental sound when relevant to model performance.
Recruit the Speakers Your Model Needs
High-quality multilingual speech data starts with the right contributors. Stepes recruits and qualifies speakers according to the linguistic, geographic, technical, and project-specific requirements of each collection program.
This allows AI teams to move beyond generic voice datasets and capture speech that better reflects their intended users and deployment markets, from broad consumer populations to narrowly defined linguistic or domain requirements.
- Language and locale
- Regional accent and dialect
- Native or other specified language background
- Project-relevant speaker criteria
- Domain familiarity when required
- Recording device and microphone
- Recording environment
- Other customer-defined qualifications
Recruit
Identify contributors who match the initial project criteria.
Screen
Verify required language, locale, accent, device, or other qualifications.
Qualify
Use instructions, sample recordings, or project-specific qualification steps as appropriate.
Record
Guide approved contributors through defined scripts, scenarios, conversations, or spontaneous-speech tasks.
Validate
Review recordings against linguistic, technical, and project-specific acceptance requirements.
Built for Modern Voice AI
Stepes provides multilingual speech and conversation data for a broad range of voice-enabled AI applications, from traditional speech recognition to emerging real-time conversational systems.
Automatic Speech Recognition
Build multilingual ASR datasets using scripted, spontaneous, accented, conversational, and domain-specific speech across diverse speakers, devices, and acoustic conditions.
Text-to-Speech & Voice AI
Collect high-quality human speech for applications involving speech synthesis, pronunciation, prosody, naturalness, and multilingual voice development. For generated-voice evaluation, Stepes can also support multilingual human review.
Multilingual AI Output Review ServicesVoice Assistants & Virtual Agents
Develop voice data for assistants and agents that must recognize requests, commands, questions, task-oriented interactions, and multi-turn voice conversations across languages.
Conversational AI
Capture human conversations that reflect natural turn-taking, follow-up questions, contextual references, corrections, hesitations, and interruptions relevant to real-time voice applications.
Conversational AI Training Data ServicesContact Center & Voice Analytics
Create controlled, purpose-built speech and conversation datasets for customer-service automation, agent-assist systems, voice analytics, call routing, and intent recognition.
Spoken Language Understanding & Voice Commands
Combine voice recordings with intent, entity, semantic, and dialogue annotations for natural language understanding, voice search, smart devices, automotive systems, and other speech-enabled applications.
From Collection Brief to Training-Ready Dataset
Stepes manages multilingual voice programs through a structured workflow that connects collection requirements with speaker recruitment, recording, linguistic processing, quality assurance, and final dataset delivery.
Define the Dataset
Align languages, locales, speech types, speaker criteria, recording volume, scripts or scenarios, devices, environments, annotations, acceptance criteria, and delivery structure with your model objectives.
Recruit & Qualify Speakers
Identify contributors who match agreed language, locale, accent, technical, and other project-specific requirements, using screening and sample recordings where appropriate.
Capture Voice & Conversation Data
Guide approved speakers through scripts, scenarios, conversations, or spontaneous-speech tasks using defined recording instructions and technical requirements.
Transcribe, Annotate & Structure
Transform raw recordings through transcription, segmentation, timestamps, speaker labeling, linguistic annotation, metadata creation, and customer-defined processing.
Validate & Deliver
Apply audio, linguistic, annotation, metadata, and dataset-level checks before organizing the final delivery to the agreed naming conventions, schema, and formats.
Turn Raw Recordings Into Training-Ready Voice Data
Audio collection is often only the beginning. Stepes can transform multilingual recordings into structured datasets for model training, fine-tuning, testing, evaluation, and analytics workflows.
Native-language expertise helps maintain alignment between the spoken audio, transcripts, annotations, and metadata across languages.
Multilingual Transcription
Convert speech recordings into aligned text using project-defined conventions, including verbatim or normalized transcription, punctuation rules, disfluencies, non-speech events, and language-specific requirements.
Segmentation & Timestamps
Divide recordings into usable speech units and align text with audio through utterance-level segmentation, phrase or sentence boundaries, start and end timestamps, and audio segment identifiers.
Speaker Labeling & Diarization Support
Identify speaker turns within multi-speaker recordings and associate speech segments with the appropriate participant for conversational AI, meeting intelligence, contact-center systems, and other voice applications.
Intent & Semantic Annotation
Enrich speech transcripts with intent, named entities, dialogue functions, semantic categories, sentiment where required, topic classifications, and customer-defined labels or taxonomies.
Metadata Structuring
Organize project-approved attributes such as language, locale, accent or dialect, speaker or session identifier, device, recording environment, acoustic condition, scenario, and other customer-defined fields.
Custom Dataset Schemas
Deliver audio, transcription, annotation, and metadata using JSON, JSONL, CSV, TSV, structured spreadsheets, aligned transcripts, common audio formats, or customer-defined schemas.
Quality at Every Layer of the Voice Dataset
Speech datasets contain multiple potential sources of error. Stepes applies quality controls across the complete dataset rather than treating audio quality as the only acceptance criterion.
Speaker Qualification
Confirm that contributors meet the language, locale, accent, device, and other criteria defined for the project.
Recording Validation
Review applicable requirements such as completeness, audio clarity, clipping, background conditions, prompt completion, file integrity, and recording specifications.
Linguistic Validation
Use qualified language resources to review pronunciation, spoken content, language variant, accent or dialect requirements, and other linguistic criteria where applicable.
Transcription QA
Validate transcripts against project guidelines for accuracy, segmentation, punctuation, normalization, disfluencies, non-speech events, and other defined conventions.
Annotation QA
Review labels for consistency with the annotation taxonomy, decision rules, examples, and acceptance requirements established for the program.
Dataset-Level Validation
Check the complete delivery for missing files, metadata completeness, naming conventions, schema integrity, language consistency, duplicates, invalid records, and other project-defined requirements.
For complex programs, pilot and calibration stages can be used to validate instructions and acceptance criteria before scaling production.
Responsible Voice Data Collection
Voice data comes from people. Responsible collection therefore requires clearly defined participation, data-use, metadata, access, and handling requirements. Stepes works with customers to establish project-specific controls appropriate to the intended dataset and collection program.
Contributor Consent
Collection workflows can incorporate project-defined contributor information and consent requirements so participants understand the nature of the recording activity and the approved use of their contributions.
Defined Data Use
Voice data collection is aligned with the intended project purpose and customer requirements rather than gathering data without a defined application.
Project-Appropriate Metadata
Speaker attributes and metadata should support a genuine dataset requirement. Stepes works with customers to identify the fields needed for the program and avoid unnecessary participant information.
Controlled Access & Customer-Specific Requirements
Project data can be managed using appropriate access controls throughout collection, processing, quality review, and delivery, with workflows configured around customer-defined data access, retention, transfer, deletion, confidentiality, and other handling requirements.
Stepes SecurityStructured Voice Data, Delivered Your Way
Different AI pipelines require different combinations of recordings, transcripts, labels, metadata, and documentation. Stepes configures the final dataset around your technical requirements rather than requiring your team to adapt to one predefined delivery model.
The result is a validated multilingual dataset structured for your model-development environment.
Why Stepes for Multilingual Voice Data Collection
Building effective global voice AI requires both data operations and deep language expertise. Stepes combines multilingual knowledge, global execution, structured quality controls, and connected AI data services to help organizations develop voice datasets that reflect how users actually speak across markets.
Language-First Dataset Design
Languages differ in pronunciation, grammar, dialect, formality, conversational behavior, and regional usage. Stepes applies professional linguistic expertise throughout dataset design, speaker qualification, transcription, annotation, and validation so these differences are addressed as part of the collection process.
Targeted Global Speaker Recruitment
Build collections around the populations your application needs to understand. Stepes can recruit speakers according to language, locale, accent, dialect, device, environment, domain familiarity, and other project-relevant criteria.
Collection Through Training-Ready Delivery
Work with one multilingual partner across speaker recruitment, recording, transcription, annotation, metadata, QA, and structured delivery. Connecting these stages helps maintain alignment between the original collection requirements and the final dataset.
Enterprise Quality & Governance
Support pilots, large-scale multilingual collections, recurring data programs, and ongoing model-improvement initiatives using defined specifications, managed workflows, structured validation, and customer-specific data handling requirements.
Multilingual Voice Data Collection FAQs
Common questions about multilingual speech and audio data collection, speaker recruitment, transcription and annotation, quality controls, data handling, and project pricing.
Stepes supports scripted speech, spontaneous speech, voice commands, wake words, short utterances, two-person and multi-speaker conversations, scenario-based recordings, accent and dialect datasets, code-switched speech, and other customer-defined audio collection requirements. Projects can be designed around specific languages, locales, speakers, devices, acoustic environments, and AI use cases.
Yes. Speaker recruitment can be configured according to language, country or locale, regional accent, dialect, language background, and other project-relevant criteria. Qualification methods depend on the program and can include screening questions, language verification, sample recordings, accent or dialect review, and technical checks.
Stepes supports multilingual AI and language programs across 100+ languages. Exact voice-data availability depends on the target language and locale, speaker criteria, collection volume, device and recording requirements, and project schedule. Contact our AI data team with your target markets and collection specifications so we can evaluate the appropriate recruitment and production approach.
Yes. We can support two-person and multi-party voice collection using scripted, scenario-driven, semi-structured, or more spontaneous conversational formats. Depending on the project, recordings can capture natural turn-taking, follow-up questions, interruptions, contextual references, overlapping speech, and other conversational behaviors needed for voice AI and speech applications.
Yes. Stepes can provide an integrated workflow that combines voice collection with multilingual transcription, segmentation, timestamps, speaker labels, intent annotation, entity annotation, semantic labels, metadata, and customer-defined taxonomies. Deliverables can be structured around your existing model-development and data-processing pipeline.
Quality controls can include speaker qualification, recording validation, linguistic review, transcription QA, annotation validation, metadata checks, and final dataset-level quality control. Acceptance criteria are defined around the individual project so the QA process evaluates the attributes that matter to the intended use of the data.
Stepes can configure collection workflows around project-specific requirements for contributor information and consent, approved data use, participant metadata, access controls, confidentiality, retention, transfer, deletion, and delivery. Because requirements vary by project, geography, dataset, and intended use, these controls are defined as part of the collection program.
Pricing depends on the specific requirements of the dataset, including languages and locales, speaker criteria, number of contributors, number or duration of recordings, scripts and scenarios, devices and recording environments, recruitment complexity, transcription and annotation requirements, quality-control methodology, and delivery structure. Send us your collection specifications or a preliminary project brief, and Stepes can recommend an appropriate workflow and provide project-specific pricing.
Build the Multilingual Voice Dataset Your AI Needs
Your users speak with different accents, dialects, devices, environments, and conversational styles. Stepes helps AI teams define, collect, transcribe, annotate, validate, and deliver multilingual speech and conversational datasets around the exact languages, speakers, scenarios, acoustic conditions, and data structures their applications require.
From an initial pilot to a large-scale global collection program, we provide the multilingual expertise and structured workflows needed to turn human speech into high-quality, training-ready AI data.