What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Speech recognition
- Machine learning
Xavier Rodet mostly deals with Speech recognition, Algorithm, Artificial intelligence, Fundamental frequency and Audio signal.
He has included themes like Subspace topology, Noise and Signal processing in his Speech recognition study.
His Algorithm research is multidisciplinary, incorporating perspectives in Cepstrum, PSOLA, Distortion and Spectral envelope.
The various areas that Xavier Rodet examines in his Artificial intelligence study include Machine learning and Pattern recognition.
His Fundamental frequency research integrates issues from Estimation theory, Voice analysis, Musical and Harmonic.
His Audio signal study incorporates themes from Time–frequency representation, Segmentation and Simulation.
His most cited work include:
- Toward Automatic Music Audio Summary Generation from Signal Analysis (148 citations)
- EFFICIENT SPECTRAL ENVELOPE ESTIMATION AND ITS APPLICATION TO PITCH SHIFTING AND ENVELOPE PRESERVATION (103 citations)
- Time — Domain Formant — Wave — Function Synthesis (101 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Speech recognition, Artificial intelligence, Acoustics, Algorithm and Speech synthesis.
His Speech recognition research includes themes of Timbre and Noise.
Xavier Rodet studied Artificial intelligence and Pattern recognition that intersect with Spectrogram and Audio signal.
The Algorithm study combines topics in areas such as Phase, Fundamental frequency, Voice analysis and Signal, Signal processing.
He interconnects Audio signal processing and Harmonic in the investigation of issues within Fundamental frequency.
He combines subjects such as Cepstrum, Representation and Envelope with his study of Spectral envelope.
He most often published in these fields:
- Speech recognition (43.06%)
- Artificial intelligence (25.00%)
- Acoustics (14.35%)
What were the highlights of his more recent work (between 2008-2016)?
- Speech recognition (43.06%)
- Artificial intelligence (25.00%)
- Speech synthesis (12.50%)
In recent papers he was focusing on the following fields of study:
His main research concerns Speech recognition, Artificial intelligence, Speech synthesis, Prosody and Pattern recognition.
Xavier Rodet integrates Speech recognition and Set in his research.
The concepts of his Artificial intelligence study are interwoven with issues in Context and Computer vision.
As a member of one scientific family, Xavier Rodet mostly works in the field of Speech synthesis, focusing on Waveform and, on occasion, Time domain, Cepstrum, Smoothing and Gaussian noise.
His biological study spans a wide range of topics, including Identification, Natural language processing, Speech corpus, Chinese speech synthesis and Syllable.
His work in Pattern recognition addresses subjects such as Spectrogram, which are connected to disciplines such as Audio signal, Entropy, Change detection and Search engine indexing.
Between 2008 and 2016, his most popular works were:
- Multiple Fundamental Frequency Estimation and Polyphony Inference of Polyphonic Music Signals (83 citations)
- Phase Minimization for Glottal Model Estimation (51 citations)
- A HMM-based speech synthesis system using a new glottal source and vocal-tract separation method (27 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Speech recognition
Xavier Rodet mainly focuses on Speech recognition, Artificial intelligence, Speech synthesis, Prosody and Vocal tract.
His Speech recognition study combines topics from a wide range of disciplines, such as Fundamental frequency, Musical instrument, Noise, Envelope and Audio signal processing.
His studies in Musical instrument integrate themes in fields like Mel-frequency cepstrum and Timbre, Musical.
The various areas that he examines in his Artificial intelligence study include Time–frequency analysis, Computer vision and Pattern recognition.
The study incorporates disciplines such as Waveform, Syllable, Trajectory and Hidden Markov model in addition to Speech synthesis.
Xavier Rodet has researched Prosody in several fields, including Speech corpus, Chinese speech synthesis and Identification.
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