Search Results for author:
Found 13 papers, 5 papers with code
Audio Flamingo: A Novel Audio Language Model with Few-Shot Learning and Dialogue Abilities
Augmenting large language models (LLMs) to understand audio -- including non-speech sounds and non-verbal speech -- is critically important for diverse real-world applications of LLMs.
Scaling NVIDIA's Multi-speaker Multi-lingual TTS Systems with Zero-Shot TTS to Indic Languages
In Track 3, we utilize P-Flow to perform zero-shot TTS by training on the challenge dataset as well as external datasets.
P-Flow: A Fast and Data-Efficient Zero-Shot TTS through Speech Prompting
P-Flow comprises a speech-prompted text encoder for speaker adaptation and a flow matching generative decoder for high-quality and fast speech synthesis.
VANI: Very-lightweight Accent-controllable TTS for Native and Non-native speakers with Identity Preservation
We introduce VANI, a very lightweight multi-lingual accent controllable speech synthesis system.
Multilingual Multiaccented Multispeaker TTS with RADTTS
We work to create a multilingual speech synthesis system which can generate speech with the proper accent while retaining the characteristics of an individual voice.
Generative Modeling for Low Dimensional Speech Attributes with Neural Spline Flows
Despite recent advances in generative modeling for text-to-speech synthesis, these models do not yet have the same fine-grained adjustability of pitch-conditioned deterministic models such as FastPitch and FastSpeech2.
One TTS Alignment To Rule Them All
However, these alignments tend to be brittle and often fail to generalize to long utterances and out-of-domain text, leading to missing or repeating words.
RAD-TTS: Parallel Flow-Based TTS with Robust Alignment Learning and Diverse Synthesis
This work introduces a predominantly parallel, end-to-end TTS model based on normalizing flows.
Relation Extraction with Contextualized Relation Embedding (CRE)
This paper proposes an architecture for the relation extraction task that integrates semantic information with knowledge base modeling in a novel manner.
An Ensemble of Humour, Sarcasm, and Hate Speechfor Sentiment Classification in Online Reviews
A qualitative analysis reveals that the conjunctive approach can better capture the nuances of sentiment as expressed in online reviews.
NELS-Never-Ending Learner of Sounds
Sounds are essential to how humans perceive and interact with the world.
Framework for evaluation of sound event detection in web videos
The framework crawls videos using search queries corresponding to 78 sound event labels drawn from three datasets.
An Approach for Self-Training Audio Event Detectors Using Web Data
The audio event detectors are trained on the labeled audio and ran on the unlabeled audio downloaded from YouTube.
