• Publications
  • Influence
The Million Song Dataset
TLDR
We introduce the Million Song Dataset, a freely-available collection of audio features and metadata for a million contemporary popular music tracks. Expand
  • 946
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Audio Set: An ontology and human-labeled dataset for audio events
TLDR
We present Audio Set, a large-scale dataset of manually-annotated audio events that endeavors to bridge the gap in data availability between image and audio research. Expand
  • 793
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CNN architectures for large-scale audio classification
TLDR
We use various CNN architectures to classify soundtracks of a dataset of 70M training videos (5.24 million hours) with 30,871 video-level labels. Expand
  • 837
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The ICSI Meeting Corpus
TLDR
We have collected a corpus of data from natural meetings that occurred at the International Computer Science Institute in Berkeley, California over the last three years. Expand
  • 652
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Tandem connectionist feature extraction for conventional HMM systems
TLDR
We show a large improvement in word recognition performance by combining neural-net discriminative feature processing with Gaussian-mixture distribution modeling. Expand
  • 791
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Consumer video understanding: a benchmark database and an evaluation of human and machine performance
TLDR
We introduce a new consumer video database called CCV, containing 9,317 web videos over 20 semantic categories, including events like "baseball" and "parade", scenes like "beach", and objects like "cat". Expand
  • 260
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librosa: Audio and Music Signal Analysis in Python
TLDR
This document describes version 0.4.0 of librosa: a Python pack- age for audio and music signal processing. Expand
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Prediction-driven computational auditory scene analysis
  • D. Ellis
  • Psychology, Computer Science
  • 1996
TLDR
The sound of a busy environment, such as a city street, gives rise to a perception of numerous distinct events in a human listener--the 'auditory scene analysis' of the acoustic information. Expand
  • 413
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A Discriminative Model for Polyphonic Piano Transcription
We present a discriminative model for polyphonic piano transcription. Support vector machines trained on spectral features are used to classify frame-level note instances. The classifier outputs areExpand
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Model-Based Expectation-Maximization Source Separation and Localization
TLDR
This paper describes a system, referred to as model-based expectation-maximization source separation and localization (MESSL), for separating and localizing multiple sound sources from an underdetermined reverberant two-channel recording. Expand
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