Digital Audio Signal Processing Research Articles

Audio signal processing technology in Arduino controlling

In recent years, the application of audio signal processing technology is frequent, which is beneficial for developing both technologies. A significant advantage of the application of audio signal processing is allowing users to input their commands by voice, which is why it is widely used in Arduino controlling. Besides, Arduino can also be applied in audio signal processing. Because Arduino is an open-source multi-functions platform with the features of low cost, its utilization will be wider and more flexible in audio-digital signal processing and many other fields in the following time. So, the combination of these two technologies can produce more and more meaningful outcomes. This paper first introduces the technical features and application scenarios of these two technologies respectively, and then analyzes some samples of the combination of the two technologies specifically and summarizes them in different aspects to know about the current situation of these fields. By deeply understanding the inadequacies of these projects, this paper also analyzes the future developing trends of the fields that can solve the current problems and improve the quality of the projects.

Behavioral and Electrical Modeling of a 0.5-V Third-Order Continuous-Time Sigma-Delta Modulator with FIR DAC for Audio Applications

Most mobile and wearable devices present digital audio signal processing capabilities. Since the nature of audio signals is analog, there is a need to use analog-to-digital converters (ADCs) with high-resolution for a high signal-to-noise ratio audio acquisition. This paper presents the high-level modeling and design of a continuous-time third-order sigma-delta modulator (CT-SDM) with an FIR DAC for audio devices, using a supply voltage of 0.5 V. The design is divided in three steps and is carried out using the Delta-sigma toolbox and a discrete-time to continuous-time (DT-CT) transformation. First, the schematic implementation with verilogA models is done to estimate the first-integrator amplifier specifications for the modulator to provide 14 bits of ENOB. Following, a two-stage inverter-based amplifier is designed and used to verify the design strategy. Finally, a transistor-level implementation of OTAs and comparator is done to evaluate the CT-SDM performance. An in-depth analysis and discussion are presented to explain the achieved results with those transistor-level circuits.

Wave Digital Models of Piezoelectric Transducers for Audio Applications

The number of consumer electronics devices integrating piezoelectric (PE) transducers as flat-panel loudspeakers has recently experienced a steep increase. Being very thin, in fact, PE transducers well cope with the miniaturization process that characterizes the market. However, at the same time, their reduced dimensions cause the sound pressure level to be poor at low frequencies, impairing the overall acoustic response. In this article, we derive novel efficient discrete-time models of PE transducers in the wave digital (WD) domain such that they can be integrated in the future into signal processing algorithms for audio output enhancement. WD filters are, in fact, making headway among audio digital signal processing techniques based on circuit equivalent models thanks to their efficiency, robustness, and accuracy. Starting from circuital representations of the piezo constitutive equations, we derive both lumped and distributed models. In particular, we show how it is possible to implement the frequency-dependent elements characterizing Mason’s model in the WD domain, contrary to what can be done using mainstream SPICE-like simulators. Such WD implementations come in handy for the simulation and fast prototyping of PE systems, paving the way toward the design of model-based digital signal processing algorithms for enhancing the transducer acoustic performance.

Discrete Wavelet Transform in digital audio signal processing: A case study of programming languages performance analysis

The time spent processing the test set is a crucial factor in research projects involving audio signal transforms. The present work analyzes the performance of a set of programming languages commonly used in this type of scientific research. The results showed the C and C++ languages as faster in a test suite with 8 different programming languages implementing the discrete Wavelet transform.

A Low-Cost, High-Performance Digital Signal Processor (DSP) for Audio Applications

Digital audio signal processing has become increasingly common in multimedia systems as a result of the development of general-purpose digital signal processors (DSP processors) and high-precision oversampling analog-to-digital (A/D) converters. Nevertheless, the solution based on standard DSP chips could be too expensive and power-hungry for portable and home entertainment audio systems. As a result, it is necessary to locate an alternative solution that is both low-cost and low-power. In the context of digital audio applications, this paper will describe how a DSP (Digital Signal Processor) is created, as well as how its architecture functions. The proposed digital signal processor (DSP) has six stages of pipeline with a fixed 24-bit data format, and each stage has 125 instructions. The instructions for the audio signal processing are provided in a very specific manner. Each and every command is handled within the confines of a single cycle.

Using Faust DSL to Develop Custom, Sample Accurate DSP Code and Audio Plugins for the Web Browser

The development and porting of virtual instruments or audio effects on the Web is a hot topic. Several initiatives are emerging, from industry-driven ones (e.g., Propellerhead Rack Extension running on the Web2), to more community based open-source projects. Most of them aim at adapting existing code bases (usually developed in native languages like C/C++) as well as facilitating the use of existing audio Digital Signal Processing (DSP) languages and platforms. Our two teams previously presented an open format for WebAudio Plugins coined WAP [2]. It aims at: (i) improving the interoperability of audio/MIDI plugins developed using pure Web APIs, (ii) porting existing native code bases, or (iii) using Domain Specific Languages (DSL). In this paper, we present a solution based around FAUST DSL, its Web-based editor, and the integration of a plugin GUI editor allowing to directly test, generate and deploy WAP plugins. We also evoke our collaborative work: one team hatching and improving FAUST, the other working on the recreation of tube guitar amplifiers and pedalboards within Web browsers. So as to fully illustrate the FAUST online framework, a case study is detailed with complete workflow, from the FAUST DSP source code written and tested in a fully functional online editor, to a self-contained plugin running in a separate host application.

CLSTM: Deep Feature-Based Speech Emotion Recognition Using the Hierarchical ConvLSTM Network

Artificial intelligence, deep learning, and machine learning are dominant sources to use in order to make a system smarter. Nowadays, the smart speech emotion recognition (SER) system is a basic necessity and an emerging research area of digital audio signal processing. However, SER plays an important role with many applications that are related to human–computer interactions (HCI). The existing state-of-the-art SER system has a quite low prediction performance, which needs improvement in order to make it feasible for the real-time commercial applications. The key reason for the low accuracy and the poor prediction rate is the scarceness of the data and a model configuration, which is the most challenging task to build a robust machine learning technique. In this paper, we addressed the limitations of the existing SER systems and proposed a unique artificial intelligence (AI) based system structure for the SER that utilizes the hierarchical blocks of the convolutional long short-term memory (ConvLSTM) with sequence learning. We designed four blocks of ConvLSTM, which is called the local features learning block (LFLB), in order to extract the local emotional features in a hierarchical correlation. The ConvLSTM layers are adopted for input-to-state and state-to-state transition in order to extract the spatial cues by utilizing the convolution operations. We placed four LFLBs in order to extract the spatiotemporal cues in the hierarchical correlational form speech signals using the residual learning strategy. Furthermore, we utilized a novel sequence learning strategy in order to extract the global information and adaptively adjust the relevant global feature weights according to the correlation of the input features. Finally, we used the center loss function with the softmax loss in order to produce the probability of the classes. The center loss increases the final classification results and ensures an accurate prediction as well as shows a conspicuous role in the whole proposed SER scheme. We tested the proposed system over two standard, interactive emotional dyadic motion capture (IEMOCAP) and ryerson audio visual database of emotional speech and song (RAVDESS) speech corpora, and obtained a 75% and an 80% recognition rate, respectively.

Toolkits for Real Time Digital Audio Signal Processing Teaching Laboratory

This paper describes an audio digital signal-processing toolkit that the authors develop to supplement a lecture course on digital signal processing (DSP) taught at the department of Electrical and Electronics Engineering at the University of Rwanda. In engineering education, laboratory work is a very important component for a holistic learning experience. However, even though today there is an increasing availability of programmable DSP hardware that students can largely benefit from, many poorly endowed universities cannot afford a costly full-fledged DSP laboratory. To help remedy this problem, the authors have developed C#.NET toolkits, which can be used for real-time digital audio signal processing laboratory. These toolkits can be used with any managed languages, like Visual Basic, C#, F# and managed C++. They provide frequently used modules for digital audio processing such as filtering, equalization, spectrum analysis, audio playback, and sound effects. It is anticipated that by creating a flexible and reusable components, students will not only learn fundamentals of DSP but also get an insight into the practicability of what they have learned in the classroom.

Modular feed-forward active noise control units for ventilation ducts.

This paper presents theoretical and experimental work on feed-forward active noise control for a ventilation duct. In particular three single channel control arrangements are investigated: (a) A classical widespread-mid-span configuration, where the control loudspeakers are located approximately half way through the duct and the reference and error microphones are placed close to inlet and outlet duct sections, respectively; (b) a compact-mid-span configuration, where both the reference and error microphones are moved close to the control loudspeakers to form a self-contained control unit, and (c) a compact-outlet configuration where the self-contained control unit is moved to the duct outlet. The two compact configurations offer self-evident practical installation and operation advantages. Moreover, the paper shows that they are characterized by much simpler control filters, which can be effectively implemented on modern audio digital signal processing boards and produce similar control performance to the classical widespread configuration.

Second-Order IIR Notch Filter Design and Implementation of Digital Signal Processing System

In this paper the AC power 50Hz power interference, we use IIR digital notch filter method for industrial frequency interference filter. From the design of IIR digital filter method proceed with, on the IIR digital notch filter simulation, the algorithm deduced, on the fixed-point DSP programming method and overflow handling problems made elaborate incisively, and in digital audio signal processing system has been applied.

Four-Channel Sub-Band Coding with Combination of [8 8 4 2] for Digital Audio Signal Processing

This paper presents the research result for the four-channel sub-band coding (SBC) with a combination of share [8 8 4 2]. The research method is based on the Wavelet multi-resolution analysis using ATRAC3 algorithm using filters designed by a novel technique of filter bank called “transit-window”. The advantages of the method are as: reduction of ripple of output amplitude response and information lossless at the interface region between two filters. Especially, under wavelet analysis with the change in the base-2 exponential partition factor from SBC [4 4 2] is to SBC [8 8 4 2] and it may be used to rec-ord/read audio and digitally broadcast on internet. The result is obtained by using the Matlab/Simulink modeling for the method.

A New Audio Watermarking Method Based on Discrete Cosine Transform with a Gray Image

Many effective watermarking algorithms have been proposed and implemented for digital images and digital video. However, a few algorithms have been proposed for audio watermarking. This is due to the fact that, human auditory system (HAS) is far more complex and sensitive than human visual system (HVS). In this research work, a new method of embedding image data into the audio signal and additive audio watermarking algorithm based on Discrete Cosine Transformation (DCT) domain is proposed. First, the original audio is transformed into DCT domain. The DCT coefficients are divided into a fixed number of subsections and the energy of each subsection is calculated. Next, watermark is generated from image by image processing algorithm. Watermarks are then embedded into selected peaks of highest energy subsection. Experimental results demonstrate that the watermark is inaudible and this algorithm is robust to common operations of digital audio signal processing, such as noise addition, re-sampling, requantization and so on. To evaluate the performance of the proposed audio watermarking method, subjective and objective quality tests including Bit Error Rate (BER) and Signal to Noise ratio (SNR) are conducted.

Case Study of a Cost-Effective on-line Learning Environment Development for Laboratory Class Enhancement

This paper reports the parallel development and formative evaluation of a web-based interactive learning course based on Matlab in the field of digital signal processing and digital audio signal processing. The challenge of creating an interactive course is discussed, and the advantages, time and cost-effectiveness are described. The architecture of system is briefly described and it can be easily extended to other fields to give students additional opportunity to an active learning. Illustrative examples of the exercises with speech signal are given in a short course description. Results of the evaluation provided a feedback for further development of the system, which lead to its enhancement and its extension. Ill. 5, bibl. 19, tabl. 1 (in English; abstracts in English and Lithuanian). http://dx.doi.org/10.5755/j01.eee.115.9.753

Dynamically Controlled Digital Audio Signal Processor

A system and method for processing multiple channel audio signals to create a realistic soundscape in a space largely independent of the number of loudspeakers and audio source channels is provided. The system includes an encoding system in the recording process and a decoding system in the local listening area.

이식형 마이크로폰과 진동체를 갖는 인공중이의 이득 보상을 위한 주파수 특성 고찰

ACROSS device, which is composed of an implantable microphone, a signal processor, and a vibrating transducer, is a fullyimplantable middle ear hearing device(F-IMEHD) for the recovery of patients with hearing loss. And since a microphone is implanted under skin and tissue at the temporal bones, the amplitude of the sound wave is attenuated by absorption and scattering. And the vibrating transducer attached to the ossicular chain caused also the different displacement from characteristic of the stapes. For the gain control of auditory signals, most of implantable hearing devices with the digital audio signal processor still apply to fitting rules of conventional hearing aid without regard to the effect of the implanted microphone and the vibrating transducer. So it should be taken into account the effect of the implantable microphone and the vibrating transducer to use the conventional audio fitting rule. The aim of this study was to measure gain characteristics caused by the implanted microphone and the vibrating transducer attached to the ossicle chains for the gain compensation of ACROSS device. Differential floating mass transducers (DFMT) of ACROSS device were clipped on four cadaver temporal bones. And after placing the DFMT on them, displacements of the ossicle chain with the DFMT operated by 1 <TEX>$mA_{peak}$</TEX> current was measured using laser Doppler vibrometer. And the sensitivity of microphones under the sampled pig skin and the skin of 3 rat back were measured by stimulus of pure tones in frequency from 0.1 to 8.9 kHz. And we confirmed that the microphone implanted under skin showed poorer frequency response in the acoustic high-frequency band than it in the low- to mid- frequency band, and the resonant frequency of the stapes vibration was changed by attaching the DFMT on the incus, the displacement of the DFMT driven with 1 <TEX>$mA_{rms}$</TEX> was higher by the amount of about 20 dB than that of cadaver's stapes driven by the sound presssure of 94 dB SPL in resonance frequency range.

Audio forensic examination

The field of audio forensics involves many topics familiar to the general audio digital signal processing (DSP) community, such as speech recognition, talker identification, and signal quality enhancement. There is potentially much to be gained by applying modern DSP theory to problems of interest to the forensics community, and this article is written to give the DSP audience some insight into the types of problems and challenges that face practitioners in audio forensic laboratories. However, this article must also present several of the frustrations and pitfalls encountered by signal processing experts when dealing with typical forensic material due to the standards and practices of the legal system.

Automated Accident Detection in Intersections via Digital Audio Signal Processing

A system for automated traffic accident detection in intersections was designed. The input to the system is a 3-s segment of audio signal. The system can be operated in two modes: the two-class and multiclass modes. The output of the two-class mode is a label of “crash” or “noncrash.” In the multiclass mode of operation, the system identifies crashes as well as several types of noncrash incidents, including normal traffic and construction sounds. The system is composed of three main signal processing stages: feature extraction, feature reduction, and classification. Five methods of feature extraction were investigated and compared; these are based on the discrete wavelet transform, fast Fourier transform, discrete cosine transform, real cepstral transform, and mel frequency cepstral transform. Statistical methods are used for feature optimization and classification. Three types of classifiers are investigated and compared; these are the nearest-mean, maximum-likelihood, and nearest-neighbor methods. The results of the study show that the optimum design uses wavelet-based features in combination with the maximum-likelihood classifier. The system is computationally inexpensive relative to the other methods investigated, and the system consistently results in accident detection accuracies of 95% to 100% when the audio signal has a signal-to-noise-ratio of at least 0 decibels.

A core-based digital audio signal processor for hi-fi audio

A second-generation core DSP suited for digital audio applications has been developed. The first DASP (digital audio signal processor) embedded with the core-DSP implements the dedicated audio, host, and external memory interfaces.

A new digital surround processing system for general A/V sources

A new surround processing algorithm is proposed for the sensible reproduction of non-encoded conventional stereo sources as well as Dolby encoded ones. The proposed method synthesizes the additional sound channels to expand the output from the conventional two channels to four or five. The directivity of auditory events is enhanced by the direction enhancement algorithm whose performance can be optimized to both cases of Dolby encoded and non-encoded sources. Also, spectral balance among the channels is tuned up to minimize the defects arising from processes such as coloration of timbre. A surround processing system based on the proposed method was implemented using a custom DASP (digital audio signal processor) chip and showed a much satisfactory performance for the various non-encoded sources as well as Dolby encoded sources.

Machine Tongues XV: Three Packages for Software Sound Synthesis

The origin of the technology and methodology of modern computer music is certainly the Music V family of software sound synthesis systems developed since the late 1950s. In the “old days,” this consisted of batch computer processing of musical programs expressed in terms of instrument definitions (programs) and score note lists (input data), generating sampled sound output data to off-line storage for later performance. The noticeable rekindling of interest in programs and languages for software sound synthesis (SWSS) and software digital audio signal processing (DSP) using general-purpose computers is due to a number of factors, not least among them the dramatic increase in the power of personal workstations over the last five years. There are currently three widely-used, portable, C-language SWSS tools: (in alphabetical order) cmix (Lansky 1990), cmusic (Moore 1990), and Csound (Vercoe 1991). This article will discuss the technology of SWSS and then present and compare these three systems. It is divided into three parts; the first introduces SWSS in terms of progressive examples. Part two compares the three systems using the same two instrument/score examples written in each of them. The final section presents informal benchmark tests of the systems run on two different hardware platforms—a Sun Microsystems SPARCstation-2 IPX and a Next Computer Inc. TurboCube machine—and subjective comments on various features of the languages and programming environments of stateof-the-art SWSS software. This author’s connection with this topic is that of extensive experience with several different SWSS systems over the last 15 years, starting with MUS10 and including all three compared here: Csound (in the form of Music-11 initially) at the CMRS studio in Salzburg (Pope 1982); cmusic in the CARL environment at PCS/Cadmus computers in Munich (Pope 1986); and more recently a combination of cmix, Csound, and various vocoder software packages with user interfaces written in Smalltalk-80 at the CCRMA Center for Computer Research in Music and Acoustics at Stanford University (Pope