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Found 7 papers, 1 papers with code
Creating Personalized Synthetic Voices from Articulation Impaired Speech Using Augmented Reconstruction Loss
Experimental results on a real case of tongue cancer patient confirm that the synthetic voice achieves comparable articulation quality to unimpaired natural speech, while effectively maintaining the target speaker's individuality.
Creating Personalized Synthetic Voices from Post-Glossectomy Speech with Guided Diffusion Models
Specifically, a diffusion-based speech synthesis model is trained on original recordings, to capture and preserve the target speaker's original articulation style.
Diffusion-Based Mel-Spectrogram Enhancement for Personalized Speech Synthesis with Found Data
One way to address this problem is to pre-enhance the speech with an enhancement model and then use the enhanced data for text-to-speech (TTS) model training.
Convolution-Based Channel-Frequency Attention for Text-Independent Speaker Verification
The weights are imposed on the input features to improve the representation ability for speaker modeling.
Transport-Oriented Feature Aggregation for Speaker Embedding Learning
Pooling is needed to aggregate frame-level features into utterance-level representations for speaker modeling.
Learnable Frequency Filters for Speech Feature Extraction in Speaker Verification
There is no reason to expect that these features are optimal for all different tasks, including speaker verification (SV).
Improving End-to-End Speech-to-Intent Classification with Reptile
In this paper, we suggest improving the generalization performance of SLU models with a non-standard learning algorithm, Reptile.
Ranked #12 on
Spoken Language Understanding
on Fluent Speech Commands
(using extra training data)
