Exploració per autor "Jauk, Igor"

Ara es mostren els items 1-7 de 7

    • Acoustic feature prediction from semantic features for expressive speech using deep neural networks 

      Jauk, Igor; Bonafonte Cávez, Antonio; Pascual, Santiago (Institute of Electrical and Electronics Engineers (IEEE), 2016)
      Text en actes de congrés
      Accés restringit per política de l'editorial
      The goal of the study is to predict acoustic features of expressive speech from semantic vector space representations. Though a lot of successful work was invested in expressiveness analysis and prediction, the results ...

    • Corpus for cyberbullying prevention 

      Moreno Bilbao, M. Asunción; Bonafonte Cávez, Antonio; Jauk, Igor; Tarrés, Laia; Pereira, Victor (International Speech Communication Association (ISCA), 2018)
      Text en actes de congrés
      Accés obert
      Cyberbullying is the use of digital media to harass a person or group of people, through personal attacks, disclosure of confidential or false information, among other means. That is to say, it ...

    • Creating expressive synthetic voices by unsupervised clustering of audiobooks 

      Jauk, Igor; Bonafonte Cávez, Antonio; López Otero, Paula; Docio Fernández, Laura (International Speech Communication Association (ISCA), 2015)
      Comunicació de congrés
      Accés restringit per política de l'editorial
      In this work we design an approach for automatic feature selection and voice creation for expressive synthesis. Our approach is guided by two main goals: (1) increasing the flexibility of expressive voice creation and (2) ...

    • Direct expressive voice training based on semantic selection 

      Jauk, Igor; Bonafonte Cávez, Antonio (International Speech Communication Association (ISCA), 2016)
      Text en actes de congrés
      Accés restringit per política de l'editorial
      This work aims at creating expressive voices from audiobooks using semantic selection. First, for each utterance of the audiobook an acoustic feature vector is extracted, including iVectors built on MFCC and on F0 ...

    • Expressive speech synthesis using sentiment embeddings 

      Jauk, Igor; Lorenzo Trueba, J.; Yamagishi, J.; Bonafonte Cávez, Antonio (International Speech Communication Association (ISCA), 2018)
      Text en actes de congrés
      Accés obert
      In this paper we present a DNN based speech synthesis system trained on an audiobook including sentiment features predicted by the Stanford sentiment parser. The baseline system uses DNN to predict acoustic parameters based ...

    • Prosodic and spectral iVectors for expressive speech synthesis 

      Jauk, Igor; Bonafonte Cávez, Antonio (Institute of Electrical and Electronics Engineers (IEEE), 2016)
      Comunicació de congrés
      Accés obert
      This work presents a study on the suitability of prosodic andacoustic features, with a special focus on i-vectors, in expressivespeech analysis and synthesis. For each utterance of two dif-ferent databases, a laboratory ...

    • Unsupervised learning for expressive speech synthesis 

      Jauk, Igor (Universitat Politècnica de Catalunya, 2017-09-12)
      Tesi
      Accés obert
      Nowadays, especially with the upswing of neural networks, speech synthesis is almost totally data driven. The goal of this thesis is to provide methods for automatic and unsupervised learning from data for expressive speech ...