Cricket sounds are usually regarded as pleasant and, thus, can be used as suitable test signals in psychoacoustic experiments assessing the human listening acuity to specific temporal and spectral features. In addition, the simple structure of cricket sounds makes them prone to reverse engineering such that they can be analyzed and re-synthesized with desired alterations in their defining parameters. This paper describes cricket sounds from a parametric point of view, characterizes their main temporal and spectral features, namely jitter, shimmer and frequency sweeps, and explains a re-synthesis process generating modified natural cricket sounds. These are subsequently used in listening tests helping to shed light on the sound identification and discrimination capabilities of humans that are important, for example, in voice recognition.

Harmonic representation models are widely used, notably in speech coding and synthesis. In this paper, we describe two fully parametric harmonic representation and signal reconstruction alternatives that rely on a shift-invariant harmonic phase model and that implement accurate frame-based synthesis in the frequency-domain, and accurate pitch pulse-based synthesis in the time-domain. We use natural spoken and sung voice signals in order to assess the objective and subjective quality of both alternatives when parameters are exact, and when they are replaced by compact and shift-invariant harmonic phase and magnitude approximation models. We highlight the flexibility of these models and present results indicating that not only does the compact shift-invariant phase model cause a smaller impact than that caused by harmonic magnitude modeling, but it also compares favorably to results presented in the literature.

This paper presents a new method for multiple fundamental frequency (F0) estimation on piano recordings. We propose a framework based on a genetic algorithm in order to analyze the overlapping overtones and search for the most likely F0 combination. The search process is aided by adaptive spectral envelope modeling and dynamic noise level estimation: while the noise is dynamically estimated, the spectral envelope of previously recorded piano samples (internal database) is adapted in order to best match the piano played on the input signals and aid the search process for the most likely combination of F0s. For comparison, several state-of-the-art algorithms were run across various musical pieces played by different pianos and then compared using three different metrics. The proposed algorithm ranked first place on Hybrid Decay/Sustain Score metric, which has better correlation with the human hearing perception and ranked second place on both onset-only and onset–offset metrics. A previous genetic algorithm approach is also included in the comparison to show how the proposed system brings significant improvements on both quality of the results and computing time.

Current signal processing techniques do not match the astonishing ability of the Human Auditory System in recognizing isolated vowels, particularly in the case of female or child speech. As didactic and clinical interactive applications are needed using sound as the main medium of interaction, new signal features must be used that capture important perceptual cues more effectively than popular features such as formants. In this paper we propose the new concept of Perceptual Spectral Cluster (PSC) and describe its implementation. Test results are presented for child and adult speech, and indicate that features elicited by the PSC concept permit reliable and robust identification of vowels, even at high pitches.

A new time-scale expansion algorithm based on a frequency-scale modification approach combined with time interpolation is presented. The algorithm is noniterative and is constrained to a blind modification of the magnitudes and phases of the relevant spectral components of the signal, on a frame-by-frame basis. The resulting advantages and limitations are discussed. A few simplified models for signal analysis/synthesis are developed, the most critical of which concern phase and frequency estimation beyond the frequency resolution of the filterbank. The structure of the algorithm is described and its performance is illustrated with both synthetic and natural audio signals.

We present a new algorithm for time-scale expansion of audio signals that comprises: time interpolation, frequency-scale expansion and modification of a spectral representation of the signal. The algorithm relies on an accurate model of signal analysis and synthesis, and was constrained to a non-iterative modification of the magnitudes and the wrapped phases of the relevant sinusoidal components of the signal. The structure of the algorithm is described and its performance is illustrated. A few examples of time-expanded wideband speech can be found on the Internet.

Perceptual coders have proven to be highly efficient in the context of audio or video applications involving bit rate reduction. However, this efficiency is strongly limited in very low bit rate coding conditions. This paper studies the multiplicative effects of quantization in the frequency domain, when an overlapped filter bank (TDAC, time domain aliasing cancellation) is used to shape the quantization noise in a perceptually optimal way. The associated circular convolution operation generates aliased components in the time domain that are examined and subjected to minimization. A closed form expression is suggested to approximate an optimal transform window offering a desired tradeoff between the reduction of the time artifacts produced by a coarse quantization and the reduction of the stop-band leakage, relative to other transform windows commonly used.

Perceptual audio coders rely on the efficient reduction of perceptually irrelevant components of the audio signal as well as on the removal of statistical signal redundancies to achieve good coding gains. In order to reach high compression ratios without reducing the subjective quality of the encoded audio signal, it is necessary to identify critically interdependent functional units of the encoding algorithm and to jointly optimize their performance. A flexible and interactive simulation and analysis environment has been programmed to assist the development and optimization of a new perceptual audio coder. The main features of this environment will be explained and the most relevant aspects that were found to limit the encoding performance will be presented.