55 citations · 187 across the 42 of their papers we have counts for
30 papers · 1 filter
DEFINE: Exemplar-Guided Accent Control for Zero-Shot TTS
Ambuj Mehrish, Abhinaba Roy, Alex Ivanov +2
Zero-shot text-to-speech (TTS) can reproduce an unseen speaker from a short reference recording, but typically entangles speaker identity and accent within the same reference. We i…
nnAudio 2: Overcoming Dynamic Compilation Barriers and Transform Inconsistencies
Abhinaba Roy, Junyi Liang, Dorien Herremans
nnAudio is an open-source audio feature extraction toolbox for deep learning, but its use in current environments is hindered by TorchScript incompatibilities, inverse-transform ed…
APEX: Large-scale Multi-task Aesthetic-Informed Popularity Prediction for AI-Generated Music
Jaavid Aktar Husain, Dorien Herremans
Music popularity prediction has attracted growing research interest, with relevance to artists, platforms, and recommendation systems. However, the explosive rise of AI-generated m…
MERIT: Learning Disentangled Music Representations for Audio Similarity
Abhinaba Roy, Junyi Liang, Dorien Herremans
Current music similarity models typically compute a single, monolithic score, entangling distinct musical dimensions like melody, rhythm, and timbre. This limits user control and i…
Text2Score: Generating Sheet Music From Textual Prompts
Keshav Bhandari, Sungkyun Chang, Abhinaba Roy +4
Developing text-driven symbolic music generation models remains challenging due to the scarcity of aligned text-music datasets and the unreliability of automated captioning pipelin…
Aligning Generative Music AI with Human Preferences: Methods and Challenges
Dorien Herremans, Abhinaba Roy
Recent advances in generative AI for music have achieved remarkable fidelity and stylistic diversity, yet these systems often fail to align with nuanced human preferences due to th…
SonicMaster: Towards Controllable All-in-One Music Restoration and Mastering
Jan Melechovsky, Ambuj Mehrish, Abhinaba Roy +1
Music recordings often suffer from audio quality issues such as excessive reverberation, distortion, clipping, tonal imbalances, and a narrowed stereo image, especially when create…
JAM: A Tiny Flow-based Song Generator with Fine-grained Controllability and Aesthetic Alignment
Renhang Liu, Chia-Yu Hung, Navonil Majumder +5
Diffusion and flow-matching models have revolutionized automatic text-to-audio generation in recent times. These models are increasingly capable of generating high quality and fait…
SonicVerse: Multi-Task Learning for Music Feature-Informed Captioning
Anuradha Chopra, Abhinaba Roy, Dorien Herremans
Detailed captions that accurately reflect the characteristics of a music piece can enrich music databases and drive forward research in music AI. This paper introduces a multi-task…
Text2midi-InferAlign: Improving Symbolic Music Generation with Inference-Time Alignment
Abhinaba Roy, Geeta Puri, Dorien Herremans
We present Text2midi-InferAlign, a novel technique for improving symbolic music generation at inference time. Our method leverages text-to-audio alignment and music structural alig…
MelodySim: Measuring Melody-aware Music Similarity for Plagiarism Detection
Tongyu Lu, Charlotta-Marlena Geist, Jan Melechovsky +2
We propose MelodySim, a melody-aware music similarity model and dataset for plagiarism detection. First, we introduce a novel method to construct a dataset focused on melodic simil…
JamendoMaxCaps: A Large Scale Music-caption Dataset with Imputed Metadata
Abhinaba Roy, Renhang Liu, Tongyu Lu +1
We introduce JamendoMaxCaps, a large-scale music-caption dataset featuring over 362,000 freely licensed instrumental tracks from the renowned Jamendo platform. The dataset includes…
ImprovNet -- Generating Controllable Musical Improvisations with Iterative Corruption Refinement
Keshav Bhandari, Sungkyun Chang, Tongyu Lu +4
Despite deep learning's remarkable advances in style transfer across various domains, generating controllable performance-level musical style transfer for complete symbolically rep…
Text2midi: Generating Symbolic Music from Captions
Keshav Bhandari, Abhinaba Roy, Kyra Wang +3
This paper introduces text2midi, an end-to-end model to generate MIDI files from textual descriptions. Leveraging the growing popularity of multimodal generative approaches, text2m…
MIRFLEX: Music Information Retrieval Feature Library for Extraction
Anuradha Chopra, Abhinaba Roy, Dorien Herremans
This paper introduces an extendable modular system that compiles a range of music feature extraction models to aid music information retrieval research. The features include musica…
Leveraging LLM Embeddings for Cross Dataset Label Alignment and Zero Shot Music Emotion Prediction
Renhang Liu, Abhinaba Roy, Dorien Herremans
In this work, we present a novel method for music emotion recognition that leverages Large Language Model (LLM) embeddings for label alignment across multiple datasets and zero-sho…
Video2Music: Suitable Music Generation from Videos using an Affective Multimodal Transformer model
Jaeyong Kang, Soujanya Poria, Dorien Herremans
Numerous studies in the field of music generation have demonstrated impressive performance, yet virtually no models are able to directly generate music to match accompanying videos…
Jointist: Simultaneous Improvement of Multi-instrument Transcription and Music Source Separation via Joint Training
Kin Wai Cheuk, Keunwoo Choi, Qiuqiang Kong +5
In this paper, we introduce Jointist, an instrument-aware multi-instrument framework that is capable of transcribing, recognizing, and separating multiple musical instruments from…
A Domain-Knowledge-Inspired Music Embedding Space and a Novel Attention Mechanism for Symbolic Music Modeling
Z. Guo, J. Kang, D. Herremans
Following the success of the transformer architecture in the natural language domain, transformer-like architectures have been widely applied to the domain of symbolic music recent…
DiffRoll: Diffusion-based Generative Music Transcription with Unsupervised Pretraining Capability
Kin Wai Cheuk, Ryosuke Sawata, Toshimitsu Uesaka +5
In this paper we propose a novel generative approach, DiffRoll, to tackle automatic music transcription (AMT). Instead of treating AMT as a discriminative task in which the model i…
Jointist: Joint Learning for Multi-instrument Transcription and Its Applications
Kin Wai Cheuk, Keunwoo Choi, Qiuqiang Kong +5
In this paper, we introduce Jointist, an instrument-aware multi-instrument framework that is capable of transcribing, recognizing, and separating multiple musical instruments from…
Understanding Audio Features via Trainable Basis Functions
Kwan Yee Heung, Kin Wai Cheuk, Dorien Herremans
In this paper we explore the possibility of maximizing the information represented in spectrograms by making the spectrogram basis functions trainable. We experiment with two diffe…
HEAR: Holistic Evaluation of Audio Representations
Joseph Turian, Jordie Shier, Humair Raj Khan +20
What audio embedding approach generalizes best to a wide range of downstream tasks across a variety of everyday domains without fine-tuning? The aim of the HEAR benchmark is to dev…
Conditional Drums Generation using Compound Word Representations
Dimos Makris, Guo Zixun, Maximos Kaliakatsos-Papakostas +1
The field of automatic music composition has seen great progress in recent years, specifically with the invention of transformer-based architectures. When using any deep learning m…