Thomas Fillon

Evaluation of an ERB frequency scale noise reduction for hearing aids: a comparative study

Among speech enhancement methods, the Ephraim and Malah suppression rule (EMSR) has proven to be efficient in reducing the background noise while preventing from a common artefact: the musical noise. From psychoacoustic motivation, an implementation of the EMSR with a perceptually relevant frequency partition is proposed. This implementation is based on non-uniform oversampled filter-banks. The frequency resolution is nevertheless uniform on the equivalent rectangular bandwidth (ERB)-scale. Objective and subjective comparison with classical EMSR and uniform critically decimated filter-banks implementations has been achieved.

A probabilistic approach to simultaneous extraction of beats and downbeats

This paper focuses on the automatic extraction of beat structure from a musical piece. A novel statistical approach to modeling beat sequences based on the application of Hidden Markov Models (HMM) is introduced. The resulting beat labels are obtained by running the Viterbi decoder and subsequent lattice rescoring. For the observation vectors we propose a new feature set that is based on the impulsive and harmonic components of the reassigned spectrogram. Different components of observation vectors have been investigated for their efficiency. The main advantage of the proposed approach is the absence of imposed deterministic rules. All the parameters are learned from the training data, and the experimental results show the efficiency of the proposed schema.

A PUBLIC AUDIO IDENTIFICATION EVALUATION FRAMEWORK FOR BROADCAST MONITORING

This paper presents the first public framework for the evaluation of audio fingerprinting techniques. Although the domain of audio identification is very active, both in the industry and the academic world, there is at present no common basis to compare the proposed techniques. This is because corpuses and evaluation protocols differ among the authors. The framework we present here corresponds to a use-case in which audio excerpts have to be detected in a radio broadcast stream. This scenario, indeed, naturally provides a large variety of audio distortions that makes this task a real challenge for fingerprinting systems. Scoring metrics are discussed with regard to this particular scenario. We then describe a whole evaluation framework including an audio corpus, together with the related groundtruth annotation, and a toolkit for the computation of the score metrics. An example of an application of this framework is finally detailed, that took place during the evaluation campaign of the Quaero project. This evaluation framework is publicly available for download and constitutes a simple, yet thorough, platform that can be used by the community in the field of audio identification to encourage reproducible results.

A Conditional Random Field system for beat tracking

In the present work, we introduce a new probabilistic model for the task of estimating beat positions in a musical audio recording, instantiating the Conditional Random Field (CRF) framework. Our approach takes its strength from a sophisticated temporal modeling of the audio observations, accounting for local tempo variations which are readily represented in the CRF model proposed using well-chosen potentials. The system is experimentally evaluated by studying its performance on 3 datasets of 1394 music excerpts of various western music styles and comparatively to 4 reference systems in the light of 6 reference evaluation metrics. The results show that the proposed system tracks perceptively coherent pulses and is very effective in estimating the beat positions while further work is needed to find the correct salient tempo.

A flexible multi-resolution time-frequency analysis framework for audio signals

In this article, a new Constant-Q transform implementation is proposed together with a generalization of both the Short-Term Fourier Transform and the Constant-Q transform. The purpose of this generalization is to provide a discrete time-frequency analysis tool with arbitrary center frequency and frequency resolution for each bin of the transform. This new analysis framework is very flexible and can be related to many common time-frequency transforms. Furthermore, new interesting transforms with specific time-frequency resolutions can be defined. To illustrate and validate the corresponding approach, experimental results and examples are provided for different configurations.