1,721,041 research outputs found
DoA reliability for distributed acoustic tracking
No full textDistributed acoustic tracking estimates the trajectories of source positions using an acoustic sensor network. As it is often difficult to estimate the source-sensor range from individual nodes, the source positions have to be inferred from Direction of Arrival (DoA) estimates. Due to reverberation and noise, the sound field becomes increasingly diffuse with increasing source-sensor distance, leading to decreased DoA estimation accuracy. To distinguish between accurate and uncertain DoA estimates, this paper proposes to incorporate the Coherent-to-Diffuse Ratio as a measure of DoA reliability for single-source tracking. It is shown that the source positions therefore can be probabilistically triangulated by exploiting the spatial diversity of all nodes
Speaker Localization with Moving Microphone Arrays
No full textSpeaker localization algorithms often assume static
location for all sensors. This assumption simplifies the models
used, since all acoustic transfer functions are linear time invariant.
In many applications this assumption is not valid. In
this paper we address the localization challenge with moving
microphone arrays. We propose two algorithms to find the
speaker position. The first approach is a batch algorithm based
on the maximum likelihood criterion, optimized via expectationmaximization
iterations. The second approach is a particle filter
for sequential Bayesian estimation. The performance of both
approaches is evaluated and compared for simulated reverberant
audio data from a microphone array with two sensors
Source tracking using moving microphone arrays for robot audition
No full textIntuitive spoken dialogues are a prerequisite for human-robot inter-
action. In many practical situations, robots must be able to identify
and focus on sources of interest in the presence of interfering speak-
ers. Techniques such as spatial filtering and blind source separa-
tion are therefore often used, but rely on accurate knowledge of the
source location. In practice, sound emitted in enclosed environments
is subject to reverberation and noise. Hence, sound source localiza-
tion must be robust to both diffuse noise due to late reverberation, as
well as spurious detections due to early reflections. For improved
robustness against reverberation, this paper proposes a novel ap-
proach for sound source tracking that constructively exploits the spa-
tial diversity of a microphone array installed in a moving robot. In
previous work, we developed speaker localization approaches using
expectation-maximization (EM) approaches and using Bayesian ap-
proaches. In this paper we propose to combine the EM and Bayesian
approach in one framework for improved robustness against rever-
beration and noise
An exemplar-based NMF approach to audio event detection
No full textWe present a novel, exemplar-based method for audio event detection based on non-negative matrix factorisation. Building on recent work in noise robust automatic speech recognition, we model events as a linear combination of dictionary atoms, and mixtures as a linear combination of overlapping events. The weights of activated atoms in an observation serve directly as evidence for the underlying event classes. The atoms in the dictionary span multiple frames and are created by extracting all possible fixed-length exemplars from the training data. To combat data scarcity of small training datasets, we propose to artificially augment the amount of training data by linear time warping in the feature domain at multiple rates. The method is evaluated on the Office Live and Office Synthetic datasets released by the AASP Challenge on Detection and Classification of Acoustic Scenes and Events. © 2013 IEEE.status: Publishe
Temporal co-registration of simultaneous electromagnetic articulography and electroencephalography for precise articulatory and neural data alignment
No full textThis study presents a temporal co-registration method combining electromagnetic articulography (EMA) and electroencephalography (EEG) to capture the neural planning and execution phases of speech with high precision. Traditional EEG alignment based on acoustic vocal onset is often inaccurate due to the variable lag between articulatory and acoustic onsets. Our approach synchronizes EMA-derived speech kinematics with EEG data, addressing these challenges. We also examined the interaction between EMA and EEG systems, focusing on the integrity of EMA signals in the presence of EEG equipment and the electromagnetic influence of EMA on EEG signal quality. The method achieved a mean alignment delay of 2.7 ms (SD = 0.4 ms), enabling detailed analysis of pre-articulatory brain activities. Additionally, our evaluations confirmed the robustness of EMA signals and EEG event-related potentials, supporting the method's precision, feasibility, and reliability for speech planning research
Characterizing code-switching:Applying linguistic principles for metric assessment and development
No full textWith handling code-switching becoming an increasingly important topic in speech technology, driven by the expansion of low-resource and multilingual methodologies, it is vital that we recognize the diversity of code-switching as a phenomenon. We propose a framework that leverages linguistic findings as makeshift ground-truths to assess the quality and sufficiency of existing metrics designed to capture data-sets' differing code-switching styles. We also introduce a new metric, T-index, which leverages machine translation systems to capture properties of code-switched words in relation to the participating language pair. Through analysis of diverse Hindi-English and Mandarin-English datasets, we systematically explore how well these metrics align with linguistic intuition regarding code-switching richness levels in conversational versus technical domains
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
No full text“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
No full textWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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