Unto K. Laine

Splitting the unit delay [FIR/all pass filters design]

A fractional delay filter is a device for bandlimited interpolation between samples. It finds applications in numerous fields of signal processing, including communications, array processing, speech processing, and music technology. We present a comprehensive review of FIR and allpass filter design techniques for bandlimited approximation of a fractional digital delay. Emphasis is on simple and efficient methods that are well suited for fast coefficient update or continuous control of the delay value. Various new approaches are proposed and several examples are provided to illustrate the performance of the methods. We also discuss the implementation complexity of the algorithms. We focus on four applications where fractional delay filters are needed: synchronization of digital modems, incommensurate sampling rate conversion, high-resolution pitch prediction, and sound synthesis of musical instruments.

A comparison of warped and conventional linear predictive coding

Frequency-warped signal processing techniques are attractive to many wideband speech and audio applications since they have a clear connection to the frequency resolution of human hearing. A warped version of linear predictive coding (LPC) is studied. The performance of conventional and warped LPC algorithms are compared in a simulated coding system using listening tests and conventional technical measures. The results indicate that the use of warped techniques is beneficial especially in wideband coding and may result in savings of one bit per sample compared to the conventional algorithm while retaining the same subjective quality.

Warped linear prediction (WLP) in speech and audio processing

A linear prediction process is applied to frequency warped signals. The warping is realized by using orthonormal FAM (frequency modulated complex exponentials) functions. The general formulation of WLP is given and effective realizations with allpass filters are studied. The application of auditory WLP to speech coding and speech recognition has given good results.<<ETX>>

A model for real-time sound synthesis of guitar on a floating-point signal processor

Algorithms that can be used to synthesize guitar sounds on a floating-point signal processor are presented. A finite impulse response (FIR) Lagrange interpolator is introduced to implement the efficient and precise fractional delay approximation that is needed to achieve arbitrary and varying-length strings. This kind of interpolation is especially good in avoiding distortion and undesirable extra effects when the string length is changing continuously during the synthesis of a sound. The interpolator can also be used in other cases, e.g. in transmission-line modeling of acoustic tube resonators in wind instruments and for vocal tract models in speech synthesis. In addition to the interpolation principle, the implementation of the guitar string model on the TMS320C30 floating-point signal processor is described.<<ETX>>

Warped filters and their audio applications

An inherent property of many DSP algorithms is that they tend to exhibit uniform frequency resolution from zero to the Nyquist frequency. This is a direct consequence of using unit delays as building blocks; a frequency independent delay implies uniform frequency resolution. In audio applications, however, this is often an undesirable feature since the response properties are typically specified and measured on a logarithmic scale, following the behavior of the human auditory system. We present an overview of warped filters and DSP techniques which can be designed to better match the audio and auditory criteria. Audio applications, including modeling of auditory and musical phenomena, equalization techniques, auralization, and audio coding, are presented.

Realizable warped IIR filters and their properties

Digital filters where unit delays are replaced with frequency dependent delays, such as first order allpass sections, are often called warped filters since they implement filter specifications on a warped non-uniform frequency scale. Warped IIR (WIIR) filters cannot be realized directly due to delay free loops. Specific solutions have been known that make WIIR filters realizable but no general approach has been available so far. In this paper we will explore the generation of such filters, including new filter structures. The robustness and computational efficiency of WIIR filters are studied and most potential applications are discussed.

An orthogonal set of frequency and amplitude modulated (FAM) functions for variable resolution signal analysis

A general formula for defining a wide class of orthogonal functions is given. The class is based on circular sine and cosine functions which are simultaneously frequency and amplitude modulated in such a way that they remain orthogonal. This is achieved with any choice of FM or AM function. The class, which is called FAM functions, offers a practical and flexible tool for signal processing. They have been used to produce nonuniform resolution auditory spectrograms. The achieved time-frequency resolution is of very high quality. The preliminary results show that they are approaching the theoretical limit given for the Delta f- Delta t product. The orthogonality of the FAM functions is proved, how a complex orthogonal auditory transform (OAT) can be realized by FAMs is described, and a method for constructing a complex orthogonal one Bark filter bank for signal analysis and psychoacoustic experimentation is given.<<ETX>>

Blind Segmentation of Speech Using Non-Linear Filtering Methods

Automated segmentation of speech into phone-sized units has been a subject of study for over 30 years, as it plays a central role in many speech processing and ASR applications. While segmentation by hand is relatively precise, it is also extremely laborious and tedious. This is one reason why automated methods are widely utilized. For example, phonetic analysis of speech (Mermelstein, 1975), audio content classification (Zhang & Kuo, 1999), and word recognition (Antal, 2004) utilize segmentation for dividing continuous audio signals into discrete, non-overlapping units in order to provide structural descriptions for the different parts of a processed signal. In the field of automatic segmentation of speech, the best results have so far been achieved with semi-automatic HMMs that require prior training (see, e.g., Makhoul & Schwartz, 1994). Algorithms using additional linguistic information like phonetic annotation during the segmentation process are often also effective (e.g., Hemert, 1991). The use of these types of algorithms is well justified for several different purposes, but extensive training may not always be possible, nor may adequately rich descriptions of speech material be available, for instance, in real-time applications. Training of the algorithms also imposes limitations to the material that can be segmented effectively, with the results being highly dependent on, e.g., the language and vocabulary of the training and target material. Therefore, several researchers have concurrently worked on blind speech segmentation methods that do not require any external or prior knowledge regarding the speech to be segmented (Almpanidis & Kotropoulos, 2008; Aversano et al., 2001; Cherniz et al., 2007; Esposito & Aversano, 2005; Estevan et al., 2007; Sharma & Mammone, 1996). These so called blind segmentation algorithms have many potential applications in the field of speech processing that are complementary to supervised segmentation, since they do not need to be trained extensively on carefully prepared speech material. As an important property, blind algorithms do not necessarily make assumptions about underlying signal conditions whereas in trained algorithms possible mismatches between training data and processed input cause problems and errors in segmentation, e.g., due to changes in background noise conditions or microphone properties. Blind methods also provide a valuable tool for investigating speech from a basic level such as phonetic research, they are language independent, and they can be used as a processing step in self-learning agents attempting to make sense of sensory input where externally supplied linguistic knowledge cannot be used (e.g., Rasanen & Driesen, 2009; Rasanen et al., 2008).

Model and filter circuit for modeling an acoustic sound channel, uses of the model, and speech synthesizer applying the model

Speech and music phonation formed by spectral formants is synthesized by a composite filter containing parallel filters in cascade. The composite filter design is generated by partial-function expansion of the approximate sound channel transfer function ##EQU1## and the composite filter is implemented with mutually adjacent formants in cascade filter elements.

An experimental audio codec based on warped linear prediction of complex valued signals

Bark-scale warped linear prediction (WLP) is a very potential core for a monophonic perceptual audio codec. In the current paper the WLP scheme is extended for processing complex valued signals (CWLP). Three different methods of converting a stereo signal to one complex valued signal are introduced. The philosophy behind the coding scheme is to integrate some aspects of modern wideband audio coding (e.g. perceptuality and stereo signal processing) into one computational element in order to find a more holistic and economic way of processing.