Expert Audio Data Built for Frontier Standards
Structured datasets for ASR, TTS, voice cloning, and audio-to-audio tasks. Start with sample data to validate fit before scaling to a full pack.
Training LLMs to understand and generate human speech
Turing’s audio data packs are designed for robust speech modeling across noisy, multilingual, and emotionally expressive contexts. Built for SFT, RLHF, and evaluation workflows, these datasets include structured prompts, response pairs, and acoustic diversity. From speech-to-text transcription to expressive voice generation, these packs stress-test models where fluency, tone, and real-world variability matter most.
Structured datasets for speech interaction and generation
Each data pack is available as a sample dataset. Samples are designed to validate scope and quality before engagement on full volumes.
ASR (noisy prompts)
Text-to-speech
Voice cloning
Full-duplex audio to audio
Audio grounding for reasoning tasks
Emotion detection and generation
Instruction following
Audio SFT
Standards trusted by frontier AI labs
Accelerate voice-based reasoning in your LLM
R&D-driven standards
Criteria and taxonomies co-defined for training and evaluation.
Transparent, auditable pipelines
Diarized, timestamped, labeled, and versioned from raw audio to formatted pack.
Elite, domain-specific talent
1000+ voice trainers, linguists, and annotation SMEs across 60+ languages.
Human-in-the-loop + AI feedback loops
Combined review to catch edge cases and ensure reproducibility.
Accelerate voice-based reasoning in your LLM
Talk to our experts and explore how Turing can accelerate your speech model training, alignment, or evaluation.
Ready to expand your model capabilities with expert data?
Get data built for post-training improvement, from SWE-Bench-style issue sets to multimodal UI gyms.