Langhui Technology's audio and speech AI data services cover the full stack — expressive TTS synthesis, ASR transcription, emotion detection, paralinguistic annotation, and voice biometrics. Built on a 10,000+ hour high-quality speech corpus spanning 500+ global languages and dialects, we infuse conversational AI, in-vehicle assistants, speech translation, and accessibility products with the latest 2026 voice-research breakthroughs.
Tracking the voice-AI research roadmaps of OpenAI, ElevenLabs, Google DeepMind, Meta FAIR, and other leading global labs, Langhui's voice-expert team continuously translates the latest breakthroughs into high-quality, production-ready training and evaluation data at scale.
In 2026, GPT-4o's real-time voice-conversation mode reached full commercial deployment. End-to-end neural codecs push average response latency down to 320ms with emotion awareness, interruption handling, and multi-turn context. Langhui supplies aligned multi-turn conversational speech data and emotional paralinguistic annotations.
ElevenLabs launched its third-generation zero-shot voice cloning — just 3 seconds of audio reconstructs a high-fidelity personalized timbre, with cross-lingual transfer and emotional-style control. Langhui builds compliantly licensed timbre-authorization corpora and multi-emotion sample data.
Google AudioGemini delivers a unified audio-understanding architecture that simultaneously processes speech, music, environmental sounds, and sound effects — with cross-modal reasoning. Langhui provides multimodal audio-event annotations and cross-modal alignment data.
Meta SeamlessM4T 2.0 delivers truly seamless speech translation — direct speech-to-speech across 100+ languages while preserving speaker timbre and emotion, with latency under 2 seconds. Langhui supplies cross-lingual aligned speech pairs and parallel corpora.
OpenAI Whisper v4 sets a new SOTA across 99 languages, dropping word-error rates to 4.2% in low-noise conditions and supporting streaming transcription with joint speaker diarization. Langhui provides multilingual ASR training sets and domain-specific evaluation data.
The EFA (Emotional Fine-grained Alignment) model delivers fine-grained emotional speech synthesis, controlling in-sentence emotional intensity curves and paralinguistic features (sighs, laughter, pauses) to approach human-level expressiveness. Langhui supplies fine-grained emotion annotations and expressive sample data.
Four core capabilities span the entire audio and speech AI data lifecycle — from TTS training data to ASR transcription annotation, emotional paralinguistic analysis, and voice biometrics — building a speech data pipeline that is production-ready, auditable, and fully traceable.
High-quality training data for speech-synthesis models across multiple emotions, styles, and languages — covering 8 major emotion categories (joy, anger, sadness, fear, surprise, disgust, neutral, excitement) and 12 styles (news broadcasting, audiobooks, customer service, advertising voice-overs, and more). Every sample includes phoneme-level alignment and prosody annotation.
High-precision ASR transcription across 500+ global languages and dialects — supporting near-field, far-field, telephony, in-vehicle, meeting, and noisy street-scene audio. Includes word-level timestamps, speaker diarization, punctuation restoration, and filler-word annotation.
Fine-grained annotation of emotion, tone, intent, and paralinguistic signals in speech — covering sentence-level emotion classification, segment-level emotional intensity, and word-level paralinguistic events (laughter, sighs, pauses, emphasis), with speaker-intent labels.
Biometric annotation for voiceprint recognition and speaker modeling — including speaker ID, age, gender, accent, dialect region, emotional state, and health conditions (e.g., cold, vocal-cord fatigue) — to build compliantly authorized voiceprint data assets.
Six ready-to-use standard voice datasets spanning multilingual ASR, emotional synthesis, dialects, meetings, voice commands, and voiceprint recognition — delivered via subscription or fully customized engagement.
High-precision ASR training data covering 100+ mainstream languages across near-field, far-field, telephony, and street-scene scenarios — with word-level timestamps, speaker diarization, and punctuation-restoration labels, aligned with Whisper / Conformer training paradigms.
High-expressiveness synthesis training data for TTS models across 8 major emotion categories — joy, anger, sadness, fear, surprise, disgust, neutral, and excitement — with acoustic-feature annotations including prosody, energy, and pitch contours.
Systematic coverage of China's seven major dialect groups (Mandarin, Wu, Xiang, Gan, Hakka, Yue, Min) and 50+ sub-dialects, with parallel Mandarin transcriptions and dialect phonetic notation — an irreplaceable training resource for dialect ASR and dialect TTS.
Real multi-speaker meeting audio — board meetings, product reviews, technical discussions, sales meetings — with speaker diarization, topic labels, decision summaries, and action-item annotations, aligned with meeting-AI training needs.
Voice-command training data for smart-home, in-vehicle, mobile-assistant, and IoT scenarios — covering 200+ intent categories, 5,000+ slot values, and dual-channel near-field/far-field recordings, optimized for on-device wake-up and command-word recognition.
A compliantly authorized voiceprint biometric dataset featuring 50,000+ speakers recorded across multiple devices, distances, and emotional states — with multi-dimensional labels such as age, gender, and accent. The gold-standard dataset for voiceprint enrollment and verification model training.
From intelligent customer service to in-vehicle assistants, from speech translation to accessibility technology, Langhui's audio and speech AI data services fit conversational AI, mobility, education, healthcare, and public-good scenarios.
For intelligent customer service in banking, telecom, e-commerce, and government, we provide multi-turn conversational speech data and emotion-detection training data — helping customer-service AI achieve 95%+ intent recognition and 90%+ emotion-recognition accuracy.
For in-vehicle voice interaction, we provide far-field noise-suppressed ASR training data, multi-dialect command sets, and in-cabin noise-scenario corpora — covering 30+ vehicle models and 12 in-cabin noise environments, helping assistants maintain 95%+ recognition at 80 km/h.
For SeamlessM4T-class seamless speech-translation systems, we provide cross-lingual aligned speech pairs, parallel corpora, and speaker-timbre-preservation data — supporting 100+ languages of direct speech-to-speech translation while preserving original emotion and timbre.
For assistive technologies serving the visually impaired, hearing impaired, and people with speech disorders, we provide high-expressiveness TTS training data and sign-language-translation speech-alignment data — enabling natural, fluid voice interactions in accessibility products.
Langhui has built a quality-assurance system that runs through the entire speech-data production pipeline — from transcription accuracy to emotion consistency, language coverage, and audio quality — with quantifiable KPIs at every dimension.
Partner with Langhui's voice-expert team to infuse your conversational AI, in-vehicle assistant, speech-translation, or accessibility product with the latest 2026 voice-research breakthroughs. Whether you need TTS training data, ASR transcription annotation, or emotional paralinguistic analysis, we tailor end-to-end solutions spanning data collection to evaluation benchmarks.