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Found 15 papers, 4 papers with code
Improving grapheme-to-phoneme conversion by learning pronunciations from speech recordings
The G2P model is used to train a multilingual phone recognition system, which then decodes speech recordings with a phonetic representation.
Multilingual context-based pronunciation learning for Text-to-Speech
Phonetic information and linguistic knowledge are an essential component of a Text-to-speech (TTS) front-end.
Comparing normalizing flows and diffusion models for prosody and acoustic modelling in text-to-speech
Neural text-to-speech systems are often optimized on L1/L2 losses, which make strong assumptions about the distributions of the target data space.
Predicting pairwise preferences between TTS audio stimuli using parallel ratings data and anti-symmetric twin neural networks
While previous work has focused on predicting listeners' ratings (mean opinion scores) of individual stimuli, we focus on the simpler task of predicting subjective preference given two speech stimuli for the same text.
Low-data? No problem: low-resource, language-agnostic conversational text-to-speech via F0-conditioned data augmentation
The availability of data in expressive styles across languages is limited, and recording sessions are costly and time consuming.
Voice Filter: Few-shot text-to-speech speaker adaptation using voice conversion as a post-processing module
It uses voice conversion (VC) as a post-processing module appended to a pre-existing high-quality TTS system and marks a conceptual shift in the existing TTS paradigm, framing the few-shot TTS problem as a VC task.
Cross-speaker style transfer for text-to-speech using data augmentation
The proposed approach relies on voice conversion to first generate high-quality data from the set of supporting expressive speakers.
Automatic audiovisual synchronisation for ultrasound tongue imaging
Our results demonstrate the strength of our approach and its ability to generalise to data from new domains.
Silent versus modal multi-speaker speech recognition from ultrasound and video
We observe that silent speech recognition from imaging data underperforms compared to modal speech recognition, likely due to a speaking-mode mismatch between training and testing.
Exploiting ultrasound tongue imaging for the automatic detection of speech articulation errors
For automatic velar fronting error detection, the best results are obtained when jointly using ultrasound and audio.
TaL: a synchronised multi-speaker corpus of ultrasound tongue imaging, audio, and lip videos
We present the Tongue and Lips corpus (TaL), a multi-speaker corpus of audio, ultrasound tongue imaging, and lip videos.
Synchronising audio and ultrasound by learning cross-modal embeddings
Audiovisual synchronisation is the task of determining the time offset between speech audio and a video recording of the articulators.
UltraSuite: A Repository of Ultrasound and Acoustic Data from Child Speech Therapy Sessions
In addition, it includes a set of annotations, some manual and some automatically produced, and software tools to process, transform and visualise the data.
Ultrasound tongue imaging for diarization and alignment of child speech therapy sessions
We investigate the automatic processing of child speech therapy sessions using ultrasound visual biofeedback, with a specific focus on complementing acoustic features with ultrasound images of the tongue for the tasks of speaker diarization and time-alignment of target words.
Speaker-independent classification of phonetic segments from raw ultrasound in child speech
Ultrasound tongue imaging (UTI) provides a convenient way to visualize the vocal tract during speech production.
