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Found 17 papers, 0 papers with code
Controllable speech synthesis by learning discrete phoneme-level prosodic representations
The final model enables fine-grained phoneme-level prosody control for all speakers contained in the training set, while maintaining the speaker identity.
Predicting phoneme-level prosody latents using AR and flow-based Prior Networks for expressive speech synthesis
A large part of the expressive speech synthesis literature focuses on learning prosodic representations of the speech signal which are then modeled by a prior distribution during inference.
Generating Gender-Ambiguous Text-to-Speech Voices
While a female voice is a common choice, there is an increasing interest in alternative approaches where the gender is ambiguous rather than clearly identifying as female or male.
Learning utterance-level representations through token-level acoustic latents prediction for Expressive Speech Synthesis
We show that the fine-grained latent space also captures coarse-grained information, which is more evident as the dimension of latent space increases in order to capture diverse prosodic representations.
Investigating Content-Aware Neural Text-To-Speech MOS Prediction Using Prosodic and Linguistic Features
In modern high-quality neural TTS systems, prosodic appropriateness with regard to the spoken content is a decisive factor for speech naturalness.
Cross-lingual Text-To-Speech with Flow-based Voice Conversion for Improved Pronunciation
When used in a cross-lingual setting, acoustic features are initially produced with a native speaker of the target language and then voice conversion is applied by the same model in order to convert these features to the target speaker's voice.
Fine-grained Noise Control for Multispeaker Speech Synthesis
A text-to-speech (TTS) model typically factorizes speech attributes such as content, speaker and prosody into disentangled representations. Recent works aim to additionally model the acoustic conditions explicitly, in order to disentangle the primary speech factors, i. e. linguistic content, prosody and timbre from any residual factors, such as recording conditions and background noise. This paper proposes unsupervised, interpretable and fine-grained noise and prosody modeling.
Karaoker: Alignment-free singing voice synthesis with speech training data
Existing singing voice synthesis models (SVS) are usually trained on singing data and depend on either error-prone time-alignment and duration features or explicit music score information.
Self-supervised learning for robust voice cloning
This method enables us to train our model in an unlabeled multispeaker dataset as well as use unseen speaker embeddings to copy a speaker's voice.
SOMOS: The Samsung Open MOS Dataset for the Evaluation of Neural Text-to-Speech Synthesis
In this work, we present the SOMOS dataset, the first large-scale mean opinion scores (MOS) dataset consisting of solely neural text-to-speech (TTS) samples.
Bunched LPCNet2: Efficient Neural Vocoders Covering Devices from Cloud to Edge
Text-to-Speech (TTS) services that run on edge devices have many advantages compared to cloud TTS, e. g., latency and privacy issues.
Improved Prosodic Clustering for Multispeaker and Speaker-independent Phoneme-level Prosody Control
This paper presents a method for phoneme-level prosody control of F0 and duration on a multispeaker text-to-speech setup, which is based on prosodic clustering.
Word-Level Style Control for Expressive, Non-attentive Speech Synthesis
This paper presents an expressive speech synthesis architecture for modeling and controlling the speaking style at a word level.
Prosodic Clustering for Phoneme-level Prosody Control in End-to-End Speech Synthesis
This paper presents a method for controlling the prosody at the phoneme level in an autoregressive attention-based text-to-speech system.
High Quality Streaming Speech Synthesis with Low, Sentence-Length-Independent Latency
This paper presents an end-to-end text-to-speech system with low latency on a CPU, suitable for real-time applications.
Cross-lingual Low Resource Speaker Adaptation Using Phonological Features
Subsequently, we fine-tune the model with very limited data of a new speaker's voice in either a seen or an unseen language, and achieve synthetic speech of equal quality, while preserving the target speaker's identity.
Rapping-Singing Voice Synthesis based on Phoneme-level Prosody Control
In this paper, a text-to-rapping/singing system is introduced, which can be adapted to any speaker's voice.
