An Online Solution for Localisation, Tracking and Separation of Moving Speech Sources

The problem of separating a time varying number of speech sources in a room is difficult to solve. The challenge lies in estimating the number and the location of these speech sources. Furthermore, the tracked speech sources need to be separated. This thesis proposes a solution which utilises the Random Finite Set approach to estimate the number and location of these speech sources and subsequently separate the speech source mixture via time frequency masking

Multiple source localization using spherical microphone arrays

Direction-of-Arrival (DOA) estimation is a fundamental task in acoustic signal processing and is used in source separation, localization, tracking, environment mapping, speech enhancement and dereverberation. In applications such as hearing aids, robot audition, teleconferencing and meeting diarization, the presence of multiple simultaneously active sources often occurs. Therefore DOA estimation which is robust to Multi-Source (MS) scenarios is of particular importance. In the past decade, interest in Spherical Microphone Arrays (SMAs) has been rapidly grown due to its ability to analyse the sound field with equal resolution in all directions. Such symmetry makes SMAs suitable for applications in robot audition where potential variety of heights and positions of the talkers are expected. Acoustic signal processing for SMAs is often formulated in the Spherical Harmonic Domain (SHD) which describes the sound field in a form that is independent of the geometry of the SMA. DOA estimation methods for the real-world scenarios address one or more performance degrading factors such as noise, reverberation, multi-source activity or tackled problems such as source counting or reducing computational complexity. This thesis addresses various problems in MS DOA estimation for speech sources each of which focuses on one or more performance degrading factor(s). Firstly a narrowband DOA estimator is proposed utilizing high order spatial information in two computationally efficient ways. Secondly, an autonomous source counting technique is proposed which uses density-based clustering in an evolutionary framework. Thirdly, a confidence metric for validity of Single Source (SS) assumption in a Time-Frequency (TF) bin is proposed. It is based on MS assumption in a short time interval where the number and the TF bin of active sources are adaptively estimated. Finally two analytical narrowband MS DOA estimators are proposed based on MS assumption in a TF bin. The proposed methods are evaluated using simulations and real recordings. Each proposed technique outperforms comparative baseline methods and performs at least as accurately as the state-of-the-art.Open Acces

A room acoustics measurement system using non-invasive microphone arrays

This thesis summarises research into adaptive room correction for small rooms and pre-recorded material, for example music of films. A measurement system to predict the sound at a remote location within a room, without a microphone at that location was investigated. This would allow the sound within a room to be adaptively manipulated to ensure that all listeners received optimum sound, therefore increasing their enjoyment. The solution presented used small microphone arrays, mounted on the room's walls. A unique geometry and processing system was designed, incorporating three processing stages, temporal, spatial and spectral. The temporal processing identifies individual reflection arrival times from the recorded data. Spatial processing estimates the angles of arrival of the reflections so that the three-dimensional coordinates of the reflections' origin can be calculated. The spectral processing then estimates the frequency response of the reflection. These estimates allow a mathematical model of the room to be calculated, based on the acoustic measurements made in the actual room. The model can then be used to predict the sound at different locations within the room. A simulated model of a room was produced to allow fast development of algorithms. Measurements in real rooms were then conducted and analysed to verify the theoretical models developed and to aid further development of the system. Results from these measurements and simulations, for each processing stage are presented

Äänikentän tila-analyysi parametrista tilaäänentoistoa varten käyttäen harvoja mikrofoniasetelmia

In spatial audio capturing the aim is to store information about the sound field so that the sound field can be reproduced without a perceptual difference to the original. The need for this is in applications like virtual reality and teleconferencing. Traditionally the sound field has been captured with a B-format microphone, but it is not always a feasible solution due to size and cost constraints. Alternatively, also arrays of omnidirectional microphones can be utilized and they are often used in devices like mobile phones. If the microphone array is sparse, i.e., the microphone spacings are relatively large, the analysis of the sound Direction of Arrival (DoA) becomes ambiguous in higher frequencies. This is due to spatial aliasing, which is a common problem in narrowband DoA estimation. In this thesis the spatial aliasing problem was examined and its effect on DoA estimation and spatial sound synthesis with Directional Audio Coding (DirAC) was studied. The aim was to find methods for unambiguous narrowband DoA estimation. The current State of the Art methods can remove aliased estimates but are not capable of estimating the DoA with the optimal Time-Frequency resolution. In this thesis similar results were obtained with parameter extrapolation when only a single broadband source exists. The main contribution of this thesis was the development of a correlation-based method. The developed method utilizes pre-known, array-specific information on aliasing in each DoA and frequency. The correlation-based method was tested and found to be the best option to overcome the problem of spatial aliasing. This method was able to resolve spatial aliasing even with multiple sources or when the source’s frequency content is completely above the spatial aliasing frequency. In a listening test it was found that the correlation-based method could provide a major improvement to the DirAC synthesized spatial image quality when compared to an aliased estimator.Tilaäänen tallentamisessa tavoitteena on tallentaa äänikentän ominaisuudet siten, että äänikenttä pystytään jälkikäteen syntetisoimaan ilman kuuloaistilla havaittavaa eroa alkuperäiseen. Tarve tälle löytyy erilaisista sovelluksista, kuten virtuaalitodellisuudesta ja telekonferensseista. Perinteisesti äänikentän ominaisuuksia on tallennettu B-formaatti mikrofonilla, jonka käyttö ei kuitenkaan aina ole koko- ja kustannussyistä mahdollista. Vaihtoehtoisesti voidaan käyttää myös pallokuvioisista mikrofoneista koostuvia mikrofoniasetelmia. Mikäli mikrofonien väliset etäisyydet ovat liian suuria, eli asetelma on harva, tulee äänen saapumissuunnan selvittämisestä epäselvää korkeammilla taajuuksilla. Tämä johtuu ilmiöstä nimeltä tilallinen laskostuminen. Tämän diplomityön tarkoituksena oli tutkia tilallisen laskostumisen ilmiötä, sen vaikutusta saapumissuunnan arviointiin sekä tilaäänisynteesiin Directional Audio Coding (DirAC) -menetelmällä. Lisäksi tutkittiin menetelmiä, joiden avulla äänen saapumissuunta voitaisiin selvittää oikein myös tilallisen laskostumisen läsnä ollessa. Työssä havaittiin, että nykyiset ratkaisut laskostumisongelmaan eivät kykene tuottamaan oikeita suunta-arvioita optimaalisella aikataajuusresoluutiolla. Tässä työssä samantapaisia tuloksia saatiin laajakaistaisen äänilähteen tapauksessa ekstrapoloimalla suunta-arvioita laskostumisen rajataajuuden alapuolelta. Työn pääosuus oli kehittää korrelaatioon perustuva saapumissuunnan arviointimenetelmä, joka kykenee tuottamaan luotettavia arvioita rajataajuuden yläpuolella ja useamman äänilähteen ympäristöissä. Kyseinen menetelmä hyödyntää mikrofoniasetelmalle ominaista, saapumissuunnasta ja taajuudesta riippuvaista laskostumiskuviota. Kuuntelukokeessa havaittiin, että korrelaatioon perustuva menetelmä voi tuoda huomattavan parannuksen syntetisoidun tilaäänikuvan laatuun verrattuna synteesiin laskostuneilla suunta-arvioilla