Blog(4)

• MELS-TTS: Multi-Emotion Multi-Lingual Multi-Speaker Text-To-Speech System via Disentangled Style Tokens

  In the swiftly progressing domain of neural text-to-speech (TTS) systems, the quest for creating human-like speech has witnessed remarkable strides. Recent advancements have opened avenues for TTS systems capable of not only mimicking human speech but also encapsulating the nuances of emotions and linguistic diversity.

• Hierarchical Timbre-Cadence Speaker Encoder for Zero-shot Speech Synthesis

  In recent years, text-to-speech (TTS) has accomplished remarkable improvement with the emergence of various end-to end TTS models [1, 2, 3]. Through these advanced models, TTS expands its field from a model built with a professional voice actor to a personalized TTS.

• [INTERSPEECH 2024 Series #3] High Fidelity Text-to-Speech Via Discrete Tokens Using Token Transducer and Group Masked Language Model

  Recently, there has been a notable shift in Text-to-Speech (TTS) research towards the adoption of discrete speech tokens as intermediate features [1-3], which presents diverse options for model architecture and inference strategies.

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Publications(3)

• Bunched LPCNet2: Efficient Neural Vocoders Covering Devices from Cloud to Edge

  AuthorSangjun Park, Kihyun Choo, Joohyung Lee, Anton V. Porov, Konstantin Osipov, June Sig Sung

  PublishedAnnual Conference of the International Speech Communication Association (INTERSPEECH)

  Date2022-09-18

• Part-of-Speech Models Compression Methods for On-device Grapheme-to-phoneme Conversion

  AuthorMarek Kubis, Pawel Skorzewski, Marcin Lewandowski 외

  PublishedInternational Conference on Acoustics, Speech, and Signal Processing (ICASSP)

  Date2022-05-22

• SEMI-SUPERVISED TRANSFER LEARNING FOR LANGUAGE EXPANSION OF END-TO-END SPEECH RECOGNITION MODELS TO LOW-RESOURCE LANGUAGES

  AuthorJiyeon Kim, Mehul Kumar, Dhananjaya Gowda, Abhinav Garg, Chanwoo Kim

  PublishedIEEE Workshop on Automatic Speech Recognition & Understanding (ASRU)

  Date2021-12-17

News(6)

• [Blog] High Fidelity Text-to-Speech Via Discrete Tokens Using Token Transducer and Group Masked Language Model

  Recently, there has been a notable shift in Text-to-Speech (TTS) research towards the adoption of discrete speech tokens as intermediate features [1-3], which presents diverse options for model architecture and inference strategies.

• [Blog] Latent Filling: Latent Space Data Augmentation for Zero-shot Speech Synthesis

  Recently, personalized AI systems have gained significant attention. In the TTS field, zero-shot text-to-speech (ZS-TTS) systems [1-7] enable users to create their own TTS systems that replicate their voices with just one utterance, without further training.

• [Blog] MELS-TTS: Multi-Emotion Multi-Lingual Multi-Speaker Text-To-Speech System via Disentangled Style Tokens

  In the swiftly progressing domain of neural text-to-speech (TTS) systems, the quest for creating human-like speech has witnessed remarkable strides. Recent advancements have opened avenues for TTS systems capable of not only mimicking human speech but also encapsulating the nuances of emotions and linguistic diversity.

View More

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