Our TTS speech synthesis datasets are built for human-like voice model training, covering global languages, diverse age groups, genders, timbres, and rich emotional intonations.
We adopt dual collection modes of professional recording studios and real daily scenarios, providing standardized voice samples including neutral, joyful, calm, serious, sad and other emotional styles, as well as narration, broadcast, customer service, and commercial voice styles. All audio is professionally polished with noise reduction, audio normalization, and prosody calibration, matched with phonetic labeling, rhythm marking, and intonation annotation to ensure natural speaking rhythm and stable timbre without mechanical distortion.
The dataset contains single words, sentences, paragraphs, and long-form manuscripts, adapting to different TTS training and cloning demands. We strictly screen speaker voice characteristics, control sample diversity and repeatability, and implement multi-round quality inspection to eliminate abnormal tones and fragmented audio.
