33 research outputs found
Binaural auditory interaction without HRTF for humanoid robots: A sensor-based control approach
International audienceNo abstrac
On Model Adaptation for Sensorimotor Control of Robots
International audienceIn this expository article, we address the problem of computing adaptive models that can be used for guiding the motion of robotic systems with uncertain action-to-perception relations. The formulation of the uncalibrated sensor-based control problem is first presented, then, various methods for building adaptive sensorimotor models are derived and analysed. Finally, the proposed methodology is exemplified with two cases of study
Estimation of the Direct-Path Relative Transfer Function for Supervised Sound-Source Localization
International audienceThis paper addresses the problem of binaural localization of a single speech source in noisy and reverberant environments. For a given binaural microphone setup, the binaural response corresponding to the direct-path propagation of a single source is a function of the source direction. In practice, this response is contaminated by noise and reverberations. The direct-path relative transfer function (DP-RTF) is defined as the ratio between the direct-path acoustic transfer function of the two channels. We propose a method to estimate the DP-RTF from the noisy and reverberant microphone signals in the short-time Fourier transform domain. First, the convolutive transfer function approximation is adopted to accurately represent the impulse response of the sensors in the STFT domain. Second, the DP-RTF is estimated by using the auto-and cross-power spectral densities at each frequency and over multiple frames. In the presence of stationary noise, an inter-frame spectral subtraction algorithm is proposed, which enables to achieve the estimation of noise-free auto-and cross-power spectral densities. Finally, the estimated DP-RTFs are concatenated across frequencies and used as a feature vector for the localization of speech source. Experiments with both simulated and real data show that the proposed localization method performs well, even under severe adverse acoustic conditions, and outperforms state-of-the-art localization methods under most of the acoustic conditions
Binaural to multichannel audio upmix
Audion tallennus- ja toistolaitteiden valikoiman kasvaessa on tÀrkeÀÀ, ettÀ kaikenlaisilla vÀlineillÀ tallennettua sekÀ syntetisoitua audiota voidaan muokata toistettavaksi kaikenlaisilla ÀÀnentoistojÀrjestelmillÀ. TÀssÀ diplomityössÀ esitellÀÀn menetelmÀ, jolla binauraalinen audiosignaali voidaan muokata toistettavaksi monikanavaisella kaiutinjÀrjestelmÀllÀ sÀilyttÀen signaalin suuntainformaation. TÀllaiselle muokkausmenetelmÀlle on tarvetta esimerkiksi etÀlÀsnÀolosovelluksissa keinona toistaa binauraalinen ÀÀnitys monikanavaisella kaiutinjÀrjestelmÀllÀ.
MenetelmÀssÀ binauraalisesta signaalista estimoidaan ensin ÀÀnilÀhteiden suunnat kÀyttÀen hyvÀksi korvien vÀlistÀ aikaeroa. Signaali muokataan monofoniseksi, ja tulosuunnan estimoinnin antama tieto tallennetaan sivuinformaationa. Monofoninen signaali muokataan sen jÀlkeen halutulle monikanavaiselle kaiutinjÀrjestelmÀlle panoroimalla se tallennetun suuntainformaation mukaisesti. KÀytÀnnössÀ menetelmÀ siis muuntaa korvien vÀlisen aikaeron kanavien vÀliseksi voimakkuuseroksi. MenetelmÀssÀ kÀytetÀÀn ja yhdistellÀÀn olemassaolevia tekniikoita tulosuunnan estimoinnille sekÀ panoroinnille.
MenetelmÀÀ testattiin vapaamuotoisessa kuuntelukokeessa, sekÀ lisÀÀmÀllÀ ÀÀninÀytteisiin binauraalista taustamelua ennen muokkausta ja arvioimalla sen vaikutusta muokatun signaalin laatuun. MenetelmÀn todettiin toimivan kelvollisesti sekÀ suuntainformaation sÀilymisen, ettÀ ÀÀnen laadun suhteen, ottaen huomioon, ettÀ sen kehitystyö on vasta aluillaan.The increasing diversity of popular audio recording and playback systems gives reasons to ensure that recordings made with any equipment, as well as any synthesised audio, can be reproduced for playback with all types of devices. In this thesis, a method is introduced for upmixing binaural audio into a multichannel format while preserving the correct spatial sensation. This type of upmix is required when a binaural recording is desired to be spatially reproduced for playback over a multichannel loudspeaker setup, a scenario typical for e.g. the prospective telepresence appliances.
In the upmix method the sound source directions are estimated from the binaural signal by using the interaural time difference. The signal is then downmixed into a monophonic format and the data given by the azimuth estimation is stored as side-information. The monophonic signal is upmixed for an arbitrary multichannel loudspeaker setup by panning it on the basis of the spatial side-information. The method, thus effectively converting interaural time differences into interchannel level differences, employs and conjoins existing techniques for azimuth estimation and discrete panning.
The method was tested in an informal listening test, as well as by adding spatial background noise into the samples before upmixing and evaluating its influence on the sound quality of the upmixed samples. The method was found to perform acceptably well in maintaining both the spatiality as well as the sound quality, regarding that much development work remains to be done
Electrophysiologic assessment of (central) auditory processing disorder in children with non-syndromic cleft lip and/or palate
Session 5aPP - Psychological and Physiological Acoustics: Auditory Function, Mechanisms, and Models (Poster Session)Cleft of the lip and/or palate is a common congenital craniofacial malformation worldwide, particularly non-syndromic cleft lip and/or palate (NSCL/P). Though middle ear deficits in this population have been universally noted in numerous studies, other auditory problems including inner ear deficits or cortical dysfunction are rarely reported. A higher prevalence of educational problems has been noted in children with NSCL/P compared to craniofacially normal children. These high level cognitive difficulties cannot be entirely attributed to peripheral hearing loss. Recently it has been suggested that children with NSCLP may be more prone to abnormalities in the auditory cortex. The aim of the present study was to investigate whether school age children with (NSCL/P) have a higher prevalence of indications of (central) auditory processing disorder [(C)APD] compared to normal age matched controls when assessed using auditory event-related potential (ERP) techniques. School children (6 to 15 years) with NSCL/P and normal controls with matched age and gender were recruited. Auditory ERP recordings included auditory brainstem response and late event-related potentials, including the P1-N1-P2 complex and P300 waveforms. Initial findings from the present study are presented and their implications for further research in this area âand clinical interventionâare outlined. © 2012 Acoustical Society of Americapublished_or_final_versio
Advanced automatic mixing tools for music
PhDThis thesis presents research on several independent systems that when
combined together can generate an automatic sound mix out of an unknown set
of multiâchannel inputs. The research explores the possibility of reproducing
the mixing decisions of a skilled audio engineer with minimal or no human
interaction. The research is restricted to nonâtime varying mixes for large room
acoustics. This research has applications in dynamic sound music concerts,
remote mixing, recording and postproduction as well as live mixing for
interactive scenes.
Currently, automated mixers are capable of saving a set of static mix
scenes that can be loaded for later use, but they lack the ability to adapt to a
different room or to a different set of inputs. In other words, they lack the
ability to automatically make mixing decisions. The automatic mixer research
depicted here distinguishes between the engineering mixing and the subjective
mixing contributions. This research aims to automate the technical tasks related
to audio mixing while freeing the audio engineer to perform the fineâtuning
involved in generating an aestheticallyâpleasing sound mix. Although the
system mainly deals with the technical constraints involved in generating an
audio mix, the developed system takes advantage of common practices
performed by sound engineers whenever possible. The system also makes use
of interâdependent channel information for controlling signal processing tasks
while aiming to maintain system stability at all times. A working
implementation of the system is described and subjective evaluation between a
human mix and the automatic mix is used to measure the success of the
automatic mixing tools
Automatic Transcription of Bass Guitar Tracks applied for Music Genre Classification and Sound Synthesis
ï»żMusiksignale bestehen in der Regel aus einer Ăberlagerung mehrerer
Einzelinstrumente. Die meisten existierenden Algorithmen zur automatischen
Transkription und Analyse von Musikaufnahmen im Forschungsfeld des Music
Information Retrieval (MIR) versuchen, semantische Information direkt aus
diesen gemischten Signalen zu extrahieren. In den letzten Jahren wurde
hÀufig beobachtet, dass die LeistungsfÀhigkeit dieser Algorithmen durch
die SignalĂŒberlagerungen und den daraus resultierenden Informationsverlust
generell limitiert ist. Ein möglicher Lösungsansatz besteht darin,
mittels Verfahren der Quellentrennung die beteiligten Instrumente vor der
Analyse klanglich zu isolieren. Die LeistungsfÀhigkeit dieser Algorithmen
ist zum aktuellen Stand der Technik jedoch nicht immer ausreichend, um eine
sehr gute Trennung der Einzelquellen zu ermöglichen. In dieser Arbeit
werden daher ausschlieĂlich isolierte Instrumentalaufnahmen untersucht,
die klanglich nicht von anderen Instrumenten ĂŒberlagert sind. Exemplarisch
werden anhand der elektrischen Bassgitarre auf die Klangerzeugung dieses
Instrumentes hin spezialisierte Analyse- und Klangsynthesealgorithmen
entwickelt und evaluiert.Im ersten Teil der vorliegenden Arbeit wird ein
Algorithmus vorgestellt, der eine automatische Transkription von
Bassgitarrenaufnahmen durchfĂŒhrt. Dabei wird das Audiosignal durch
verschiedene Klangereignisse beschrieben, welche den gespielten Noten auf
dem Instrument entsprechen. Neben den ĂŒblichen Notenparametern Anfang,
Dauer, LautstÀrke und Tonhöhe werden dabei auch instrumentenspezifische
Parameter wie die verwendeten Spieltechniken sowie die Saiten- und Bundlage
auf dem Instrument automatisch extrahiert. Evaluationsexperimente anhand
zweier neu erstellter AudiodatensÀtze belegen, dass der vorgestellte
Transkriptionsalgorithmus auf einem Datensatz von realistischen
Bassgitarrenaufnahmen eine höhere Erkennungsgenauigkeit erreichen kann als
drei existierende Algorithmen aus dem Stand der Technik. Die SchÀtzung der
instrumentenspezifischen Parameter kann insbesondere fĂŒr isolierte
Einzelnoten mit einer hohen GĂŒte durchgefĂŒhrt werden.Im zweiten Teil der
Arbeit wird untersucht, wie aus einer Notendarstellung typischer sich
wieder- holender Basslinien auf das Musikgenre geschlossen werden kann.
Dabei werden Audiomerkmale extrahiert, welche verschiedene tonale,
rhythmische, und strukturelle Eigenschaften von Basslinien quantitativ
beschreiben. Mit Hilfe eines neu erstellten Datensatzes von 520 typischen
Basslinien aus 13 verschiedenen Musikgenres wurden drei verschiedene
AnsĂ€tze fĂŒr die automatische Genreklassifikation verglichen. Dabei zeigte
sich, dass mit Hilfe eines regelbasierten Klassifikationsverfahrens nur
Anhand der Analyse der Basslinie eines MusikstĂŒckes bereits eine mittlere
Erkennungsrate von 64,8 % erreicht werden konnte.Die Re-synthese der
originalen Bassspuren basierend auf den extrahierten Notenparametern wird
im dritten Teil der Arbeit untersucht. Dabei wird ein neuer
Audiosynthesealgorithmus vorgestellt, der basierend auf dem Prinzip des
Physical Modeling verschiedene Aspekte der fĂŒr die Bassgitarre
charakteristische Klangerzeugung wie Saitenanregung, DĂ€mpfung, Kollision
zwischen Saite und Bund sowie dem Tonabnehmerverhalten nachbildet.
Weiterhin wird ein parametrischerAudiokodierungsansatz diskutiert, der es
erlaubt, Bassgitarrenspuren nur anhand der ermittel- ten notenweisen
Parameter zu ĂŒbertragen um sie auf Dekoderseite wieder zu
resynthetisieren. Die Ergebnisse mehrerer Hötest belegen, dass der
vorgeschlagene Synthesealgorithmus eine Re- Synthese von
Bassgitarrenaufnahmen mit einer besseren KlangqualitÀt ermöglicht als die
Ăbertragung der Audiodaten mit existierenden Audiokodierungsverfahren, die
auf sehr geringe Bitraten ein gestellt sind.Music recordings most often consist of multiple instrument signals, which
overlap in time and frequency. In the field of Music Information Retrieval
(MIR), existing algorithms for the automatic transcription and analysis of
music recordings aim to extract semantic information from mixed audio
signals. In the last years, it was frequently observed that the algorithm
performance is limited due to the signal interference and the resulting
loss of information. One common approach to solve this problem is to first
apply source separation algorithms to isolate the present musical
instrument signals before analyzing them individually. The performance of
source separation algorithms strongly depends on the number of instruments
as well as on the amount of spectral overlap.In this thesis, isolated
instrumental tracks are analyzed in order to circumvent the challenges of
source separation. Instead, the focus is on the development of
instrument-centered signal processing algorithms for music transcription,
musical analysis, as well as sound synthesis. The electric bass guitar is
chosen as an example instrument. Its sound production principles are
closely investigated and considered in the algorithmic design.In the first
part of this thesis, an automatic music transcription algorithm for
electric bass guitar recordings will be presented. The audio signal is
interpreted as a sequence of sound events, which are described by various
parameters. In addition to the conventionally used score-level parameters
note onset, duration, loudness, and pitch, instrument-specific parameters
such as the applied instrument playing techniques and the geometric
position on the instrument fretboard will be extracted. Different
evaluation experiments confirmed that the proposed transcription algorithm
outperformed three state-of-the-art bass transcription algorithms for the
transcription of realistic bass guitar recordings. The estimation of the
instrument-level parameters works with high accuracy, in particular for
isolated note samples.In the second part of the thesis, it will be
investigated, whether the sole analysis of the bassline of a music piece
allows to automatically classify its music genre. Different score-based
audio features will be proposed that allow to quantify tonal, rhythmic, and
structural properties of basslines. Based on a novel data set of 520
bassline transcriptions from 13 different music genres, three approaches
for music genre classification were compared. A rule-based classification
system could achieve a mean class accuracy of 64.8 % by only taking
features into account that were extracted from the bassline of a music
piece.The re-synthesis of a bass guitar recordings using the previously
extracted note parameters will be studied in the third part of this thesis.
Based on the physical modeling of string instruments, a novel sound
synthesis algorithm tailored to the electric bass guitar will be presented.
The algorithm mimics different aspects of the instrumentâs sound
production mechanism such as string excitement, string damping, string-fret
collision, and the influence of the electro-magnetic pickup. Furthermore, a
parametric audio coding approach will be discussed that allows to encode
and transmit bass guitar tracks with a significantly smaller bit rate than
conventional audio coding algorithms do. The results of different listening
tests confirmed that a higher perceptual quality can be achieved if the
original bass guitar recordings are encoded and re-synthesized using the
proposed parametric audio codec instead of being encoded using conventional
audio codecs at very low bit rate settings