A leading North American AI technology company specializing in conversational platforms partnered with Dserve AI to scale their multilingual digital assistant product. The client was expanding into global markets and required high-quality speech training data to power their next-generation automatic speech recognition (ASR) and natural language understanding (NLU) systems.
Their goal was to build voice-enabled digital assistants capable of understanding spontaneous, real-world speech across multiple regions and languages.
Project Objective
The client aimed to accelerate the development of their multilingual speech recognition models by acquiring large-scale, diverse, and high-quality utterance datasets.
Key Objectives:
Collect and transcribe millions of single-speaker utterances (3–30 seconds each)
Support 13 global Tier-1 & Tier-2 languages
Ensure demographic and dialect diversity
Maintain audio quality standards (minimum 16kHz, preferred 44kHz)
Deliver audio files with accurate transcriptions and structured JSON metadata
Meet aggressive timelines without compromising quality
Key Challenges
Collecting utterance data at global scale while maintaining strict quality, compliance, and diversity standards posed multiple operational challenges.
| Challenge | Description |
|---|---|
| Large-Scale Data Collection | 1M+ utterances required within 8 months |
| Linguistic Diversity | 13 languages with regional dialect variations |
| Speaker Diversity | Balanced mix of age, gender, education & accent |
| Recording Conditions | Controlled & natural environments as per specification |
| Metadata Structuring | Accurate transcription with JSON metadata |
| Quality & Compliance | High acceptance rate with PII-safe processes |
Our Solution
With deep expertise in Conversational AI datasets, Dserve AI deployed a structured, scalable utterance collection and transcription workflow.
We built a multilingual pipeline involving native linguists, voice contributors, QA specialists, and data engineers to ensure precision at every stage.
Scope of Work Delivered:
Text prompt generation for each language
Recruitment of native speakers across demographics
Audio recording collection (3–30 sec per utterance)
Manual transcription & validation by expert linguists
JSON metadata creation (speaker profile, language tag, recording environment)
Multi-layer quality control & PII compliance checks
Project Metrics:
Total Audio Hours: 22,000+ hours
Languages Supported: 13
Total Utterances Delivered: 1M+
Timeline: 2–3 months
Data Acceptance Rate: >95%
Project Impact
The structured and diverse dataset enabled the client to significantly improve multilingual speech recognition accuracy.
| Impact Area | Improvement |
|---|---|
| ASR Model Accuracy | Significant boost across 13 languages |
| Intent Recognition | Improved real-world query understanding |
| Dialect Adaptation | Better handling of regional accents |
| Time-to-Market | Accelerated global product rollout |
| User Experience | More natural, human-like conversations |
With gold-standard utterance datasets delivered by Dserve AI, the client successfully launched enhanced multilingual digital assistants across new markets.
Key Business Results:
Faster AI model deployment cycle
Reduced re-training costs
Improved customer satisfaction metrics
Competitive advantage in global voice AI space
Scalable data pipeline for future language expansion
Dserve AI demonstrated exceptional execution capability in managing multilingual utterance collection at scale. Their quality standards, linguistic expertise, and ability to meet tight deadlines made them a reliable long-term partner.
— Director of AI Programs, Veritone Inc., USA United States
Why Dserve AI?
- Proven expertise in Conversational AI datasets
- Large global network of voice contributors & linguists
- Scalable data collection infrastructure
- 100% PII-compliant workflows
- Multi-layer QA ensuring >95% acceptance
- Experience working with global enterprise clients
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