{"url":"/dataset/gneutralspeech-female","name":"GneutralSpeech Female","full_name":null,"description_markdown":"A Brazilian Portuguese TTS dataset featuring a female voice\r\nrecorded with high quality in a controlled environment, with\r\nneutral emotion and more than 20 hours of recordings.\r\n with\r\nneutral emotion and more than 20 hours of recordings. Our\r\ndataset aims to facilitate transfer learning for researchers and\r\ndevelopers working on TTS applications: a highly professional\r\nneutral female voice can serve as a good warm-up stage for\r\nlearning language-specific structures, pronunciation and other\r\nnon-individual characteristics of speech, leaving to further\r\ntraining procedures only to learn the specific adaptations\r\nneeded (e.g. timbre, emotion and prosody). This can surely\r\nhelp enabling the accommodation of a more diverse range\r\nof female voices in Brazilian Portuguese. By doing so, we\r\nalso hope to contribute to the development of accessible and\r\nhigh-quality TTS systems for several use cases such as virtual\r\nassistants, audiobooks, language learning tools and accessibility solutions.\r\n\r\nPossible  use cases: \r\nTTS;\r\nVoice Conversion;\r\nASR;\r\nSpeech Enhancement","description_withheld":null,"homepage":"https://gpa-smt-ufrj.github.io/sbrt2023/intro.html","introduced_date":"2023-10-08","introduced_date_note":null,"introduced_by":{"paper":"/paper/neutral-tts-female-voice-corpus-in-brazilian","title":"Neutral TTS Female Voice Corpus in Brazilian Portuguese","first_author":"Pedro H. L. Leite","url":null},"license":{"name":"Custom","url":"https://www.kaggle.com/datasets/mediatechlab/g-neutral-speech-female"},"modalities":[{"name":"Texts","url":"/datasets/modality/texts"},{"name":"Audio","url":"/datasets/modality/audio"}],"tasks":[{"name":"Speech Enhancement","url":"/task/speech-enhancement","datasets_with_task":"/datasets/task/speech-enhancement"},{"name":"Automatic Speech Recognition (ASR)","url":"/task/automatic-speech-recognition","datasets_with_task":"/datasets/task/automatic-speech-recognition"},{"name":"Text-To-Speech Synthesis","url":"/task/text-to-speech-synthesis","datasets_with_task":"/datasets/task/text-to-speech-synthesis"},{"name":"Voice Conversion","url":"/task/voice-conversion","datasets_with_task":"/datasets/task/voice-conversion"},{"name":"Voice Cloning","url":"/task/voice-cloning","datasets_with_task":"/datasets/task/voice-cloning"}],"languages":[{"name":"Portuguese","url":"/datasets/language/portuguese"}],"variants":["GneutralSpeech Female"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}