Download The REACTION System: Automatic Sound Segmentation and Word Spotting for Verbal Reaction Time Tests Reaction tests are typical tests from the field of psychological research and communication science in which a test person is presented some stimulus like a photo, a sound, or written words. The individual has to evaluate the stimulus as fast as possible in a predefined manner and has to react by presenting the result of the evaluation. This could be by pushing a button in simple reaction tests or by saying an answer in verbal reaction tests. The reaction time between the onset of the stimulus and the onset of the response can be used as a degree of difficulty for performing the given evaluation. Compared to simple reaction tests verbal reaction tests are very powerful since the individual can simply say the answer which is the most natural way of answering. The drawback for verbal reaction tests is that today the reaction times still have to be determined manually. This means that a person has to listen through all audio recordings taken during test sessions and mark stimuli times and word beginnings one by one which is very time consuming and people-intensive. To replace the manual evaluation of reaction tests this article presents the REACTION (Reaction Time Determination) system which can automatically determine the reaction times of a test session by analyzing the audio recording of the session. The system automatically detects the onsets of stimuli as well as the onsets of answers. The recording is furthermore segmented into parts each containing one stimulus and the following reaction which further facilitates the transcription of the spoken words for a semantic evaluation.
Download Identifying function-specific prosodic cues for non-speech user interface sound design This study explores the potential of utilising certain prosodic qualities of function-specific vocal expressions in order to design effective non-speech user interface sounds. In an empirical setting, utterances with four context-situated communicative functions were produced by 20 participants. Time series of fundamental frequency (F0 ) and intensity were extracted from the utterances and analysed statistically. The results show that individual communicative functions have distinct prosodic characteristics that can be statistically modelled. By using the model, certain function-specific prosodic cues can be identified and, in turn, imitated in the design of communicative interface sounds for the corresponding communicative functions in human-computer interaction.
Download Singing Voice Separation Based on Non-Vocal Independent Component Subtraction and Amplitude Discrimination Many applications of Music Information Retrieval can benefit from effective isolation of the music sources. Earlier work by the authors led to the development of a system that is based on Azimuth Discrimination and Resynthesis (ADRess) and can extract the singing voice from reverberant stereophonic mixtures. We propose an extension to our previous method that is not based on ADRess and exploits both channels of the stereo mix more effectively. For the evaluation of the system we use a dataset that contains songs convolved during mastering as well as the mixing process (i.e. “real-world” conditions). The metrics for objective evaluation are based on bss_eval.
Download Application of non-negative matrix factorization to signal-adaptive audio effects This paper proposes novel audio effects based on manipulating an audio signal in a representation domain provided by non-negative matrix factorization (NMF). Critical-band magnitude spectrograms Y of sounds are first factorized into a product of two lower-rank matrices so that Y ≈ BG. The parameter matrices B and G are then processed in order to achieve the desired effect. Three classes of effects were investigated: 1) dynamic range compression (or expansion) of the component spectra or gains, 2) effects based on rank-ordering the components (colums of B and the corresponding rows of G) according to acoustic features extracted from them, and then weighting each component according to its rank, and 3) distortion effects based on controlling the amount of components (and thus the reconstruction error) in the above linear approximation. The subjective quality of the effects was assessed in a listening test.
Download Separation Of Speech Signal From Complex Auditory Scenes The hearing system, even in front of complex auditory scenes and in unfavourable conditions, is able to separate and recognize auditory events accurately. A great deal of effort has gone into the understanding of how, after having captured the acoustical data, the human auditory system processes them. The aim of this work is the digital implementation of the decomposition of a complex sound in separate parts as it would appear to a listener. This operation is called signal separation. In this work, the separation of speech signal from complex auditory scenes has been studied and an experimentation of the techniques that address this problem has been done.
Download A New Criterion and Associated Bit Allocation Method for Current Audio Coding Standards This paper presents a new noise-shaping criterion. Based on the new criterion, we derive an efficient bit allocation method. The bit allocation method is applicable to the current audio standards like MPEG1 Layer 3 and MPEG4 AAC. The bit allocation method has gained a speed up for more than ten and has resulted in better quality over the traditional two nested loop method presented in ISO draft. The experiments illustrated the correction of the objective measurement criterion and the new allocation has shown the deterministic method instead of the iteration method to achieve the high allocation efficiency and best quality.
Download Sound Source Separation: Azimuth Discrimination and Resynthesis In this paper we present a novel sound source separation algorithm which requires no prior knowledge, no learning, assisted or otherwise, and performs the task of separation based purely on azimuth discrimination within the stereo field. The algorithm exploits the use of the pan pot as a means to achieve image localisation within stereophonic recordings. As such, only an interaural intensity difference exists between left and right channels for a single source. We use gain scaling and phase cancellation techniques to expose frequency dependent nulls across the azimuth domain, from which source separation and resynthesis is carried out. We present results obtained from real recordings, and show that for musical recordings, the algorithm improves upon the output quality of current source separation schemes.
Download Model-based synthesis and transformation of voiced sounds In this work a glottal model loosely based on the Ishizaka and Flanagan model is proposed, where the number of parameters is drastically reduced. First, the glottal excitation waveform is estimated, together with the vocal tract filter parameters, using inverse filtering techniques. Then the estimated waveform is used in order to identify the nonlinear glottal model, represented by a closedloop configuration of two blocks: a second order resonant filter, tuned with respect to the signal pitch, and a regressor-based functional, whose coefficients are estimated via nonlinear identification techniques. The results show that an accurate identification of real data can be achieved with less than regressors of the nonlinear functional, and that an intuitive control of fundamental features, such as pitch and intensity, is allowed by acting on the physically informed parameters of the model. 10
Download Blind Separation of Monaural Signals using Complex Wavelets In this paper, a new method of blind source separation of monaural signals is presented. It is based on similarity criteria between envelopes and frequency trajectories of the components of the signal, and on its onset and offset times. The main difference with previous works is that in this paper, the input signal has been filtered using a flexible complex band pass filter bank that is a discrete version of the Complex Continuous Wavelet Transform (CCWT). Our main purpose is to show that the CCWT can be a powerful tool in blind separation, due to its strong coherence in both time and frequency domains. The presented separation algorithm is a first approximation to this important task. An example set of four synthetically mixed monaural signals have been analyzed by this method. The obtained results are promising.
Download Effective Separation of Low-Pitch Notes Using NMF Using Non-Power-of-2 Discrete Fourier Transforms Recently, non-negative matrix factorization (NMF), which is applied to decompose signals in frequency domain by means of short-time Fourier transform (STFT), is widely used in audio source separation. Separation of low-pitch notes in recordings is of significant interest. According to time-frequency uncertainty principle, it may suffer from the tradeoff between time and frequency localizations for low-pitch sounds. Furthermore, because the window function applied to the signal causes frequency spreading, separation of low-pitch notes becomes more difficult. Instead of using power-of-2 FFT, we experiment on STFT sizes corresponding to the pitches of the notes in the signals. Computer simulations using synthetic signals show that the Source to Interferences Ratio (SIR) is significantly improved without sacrificing Sources to Artifacts Ratio (SAR) and Source to Distortion Ratio (SDR). In average, at least 2 to 6 dB improvement in SIR is achieved when compared to power-of-2 FFT of similar sizes.