Rudy Rotili

• Marche Polytechnic University

This paper deals with speech enhancement in noisy reverberated environments where multiple speakers are active. The authors propose an advanced real-time speech processing front-end aimed at automatically reducing the distortions introduced by room reverberation in distant speech signals, also considering the presence of background noise, and thus...

This paper proposes a real-time person activity detection framework operating in presence of multiple sources in reverberated environments. Such a framework is composed by two main parts: The speech enhancement front-end and the activity detector. The aim of the former is to automatically reduce the distortions introduced by room reverberation in t...

This work proposes a dominance detection framework operating in reverberated environments. The framework is composed of a speech enhancement front-end, which automatically reduces the distortions introduced by room reverberation in the speech signals, and a dominance detector, which processes the enhanced signals and estimates the most and least do...

This paper proposes a real-time speech enhancement framework working in presence of multiple sources in reverberated environments. The aim is to automatically reduce the distortions introduced by room reverberation in the available distant speech signals and thus to achieve a significant improvement of speech quality for each speaker. The overall f...

This paper proposes a real-time algorithmic framework for Automatic Speech Recognition (ASR) in presence of multiple sources in reverberated environment. The addressed real-life acoustic scenario definitely asks for a robust signal processing solution to reduce the impact of source mixing and reverberation on ASR performances. Here the authors show...

Blind source separation and speech dereverberation are two important and common issues in the field of audio processing especially in the context of real meetings. In this paper a real time framework implementing a sequential source separation and speech dereverberation algorithm based on blind channel identification is taken as starting point. The...

This paper presents a conversational speech recognition system able to operate in non-stationary reverberated environments. The system is composed of a dereverberation front-end exploiting multiple distant microphones, and a speech recognition engine. The dereverberation front-end identifies a room impulse response by means of a blind channel ident...

Feature statistics normalization in the cepstral domain is one of the most performing approaches for robust automaticspeech and speaker recognition in noisy acoustic scenarios: feature coefficients are normalized by using suitable linear or nonlinear transformations in order to match the noisy speech statistics to the clean speech one. Histogram eq...

Feature statistics normalization in the cepstral domain is one of the most performing approaches for robust automatic Speech Recognition (ASR) in noisy acoustic scenarios. According to this approach, feature coefficients are normalized by using suitable linear or nonlinear transformations in order to match the noisy speech statistics to the clean s...

Blind source separation (BSS) and dereverberation have been deeply investigated due to their importance in many applications, as in image and audio processing. A two-stage approach leading to a sequential source separation and speech dereverberation algorithm based on blind channel identification (BCI) has recently appeared in literature and taken...

This paper proposes innovative multi-channel bayesian estimators in the feature-domain for robust speech recognition. Both minimum-mean-squared-error (MMSE) and maximum-a-posteriori (MAP) criteria have been explored: the related algorithms extend the multi-channel frequency-domain counterparts and generalize the single-channel feature-domain MMSE s...

Bayesian estimators, especially the Minimum Mean Square Error (MMSE) and the Maximum A Posteriori (MAP), are very popular in estimating the clean speech STFT coefficients. Recently, a similar trend has been successfully applied to speech feature enhancement for robust Automatic Speech/Speaker Recognition (ASR) applications either in the Mel, log-Me...

The SPLICE algorithm has been recently proposed in the literature to address the robustness issue in Automatic Speech Recognition (ASR). Several variants have been also proposed to improve some drawbacks of the original technique. In this presentation an innovative efficient solution is discussed: it is based on SNR estimation in the frequency or m...

The present paper deals with the Acoustic Feedback Cancellation problem and proposes a real-time implementation on Texas Instruments C6713 DSK board of two AFC algorithms, one patented and the other recently appeared in the literature. Different approaches have been followed for their porting to target, in relationship with the domain they have bee...

One of the big challenges in the field of Automatic Speech Recognition (ASR) consists in developing suitable solutions able to work properly also in adverse acoustic conditions, like in presence of additive noise and/or in reverberant rooms. Recently a certain attention has been paid to deeply integrate the noise suppressor in the feature extracti...

Developing performing speech reinforcement systems to improve the intra-cabin communication quality among car passengers in different row seats, typically degraded by the distance between speakers (for instance in SUV and mini-van) and the noise presence within the cockpit, has represented a challenging issue within the related scientific community...

Acoustic feedback is a longstanding problem in the audio processing field, occurring whenever sound is captured and reproduced in the same environment. Different control strategies have been proposed over the years, among which a feedback cancellation technique based on the prediction error method (PEM) has revealed to be performing on purpose. Rec...

In the present work the inverse filtering problem for speech dereverberation in stationary conditions is addressed. In particular we consider the presence of multiple observables which has a beneficial impact of on room transfer functions (RTFs) invertibility. In actual acoustic environments the assumed knowledge of RTFs is usually altered by the p...

In this paper, a speech-interfaced system for fostering group conversations is presented. The system captures conversation keywords and shows visual stimuli on a tabletop display. A stimulus can be a feedback to the current conversation or a cue to discuss new topics. This work describes the overall system architecture and highlights details about...