A Binaural Neuromorphic Auditory Sensor for FPGA: A Spike Signal Processing Approach

This paper presents a new architecture, design flow, and field-programmable gate array (FPGA) implementation analysis of a neuromorphic binaural auditory sensor, designed completely in the spike domain. Unlike digital cochleae that decompose audio signals using classical digital signal processing techniques, the model presented in this paper processes information directly encoded as spikes using pulse frequency modulation and provides a set of frequency-decomposed audio information using an address-event representation interface. In this case, a systematic approach to design led to a generic process for building, tuning, and implementing audio frequency decomposers with different features, facilitating synthesis with custom features. This allows researchers to implement their own parameterized neuromorphic auditory systems in a low-cost FPGA in order to study the audio processing and learning activity that takes place in the brain. In this paper, we present a 64-channel binaural neuromorphic auditory system implemented in a Virtex-5 FPGA using a commercial development board. The system was excited with a diverse set of audio signals in order to analyze its response and characterize its features. The neuromorphic auditory system response times and frequencies are reported. The experimental results of the proposed system implementation with 64-channel stereo are: a frequency range between 9.6 Hz and 14.6 kHz (adjustable), a maximum output event rate of 2.19 Mevents/s, a power consumption of 29.7 mW, the slices requirements of 11 141, and a system clock frequency of 27 MHz.Ministerio de Economía y Competitividad TEC2012-37868-C04-02Junta de Andalucía P12-TIC-130

Real-time audio spectrum analyser research, design, development and implementation using the 32 bit ARMR Cortex-M4 microcontroller

This thesis describes the design and testing of a low-cost hand-held real-time audio analyser (RTAA). This includes the design of an embedded system, the development of the firmware executed by the embedded system, and the implementation of a real-time signal processing algorithms. One of the objectives of this project was to design an alternative low-cost audio analyser to the current commercially available solutions. The device was tested with the audio standard test signal (pink noise) and was compared to the expected at-spectrum response corresponding to a balanced audio system. The design makes use of an 32-bit Reduced Instruction Set Computer (RISC) processor core (ARM Cortex-M4), namely the STM32F4 family of microcontrollers. Due to the pin compatibility of the microcontroller (designed and manufactured by STMicroelectronics), the new development board can also be upgraded with the newly released Cortex-M7 microcontroller, namely the STM32F7 family of microcontrollers. Moreover, the low-cost hardware design features 256kB Random Access Memory (RAM); on-board Micro-Electro-Mechanical System (MEMS) microphone; on-chip 12-bit Analogue-to-Digital (A/D) and Digital-to-Analogue (D/A) Converters; 3.2" Thin-Film-Transistor Liquid-Crystal Display (TFT-LCD) with a resistive touch screen sensor and SD-Card Socket. Furthermore, two additional expansion modules were designed and can extend the functionality of the designed real-time audio analyser. Firstly, an audio/video module featuring a professional 24-bit 192kHz sampling rate audio CODEC; balanced audio microphone input; unbalanced line output; three MEMS microphone inputs; headphone output; and a Video Graphics Array (VGA) controller allowing the display of the analysed audio spectrum on either a projector or monitor. The second expansion module features two external memories: 1MB Static Random Access Memory (SRAM) and 16MB Synchronous Dynamic Random Access Memory (SDRAM). While the two additional expansion modules were not completely utilised by the firmware presented in this thesis, upgrades of the real-time audio analyser firmware in future revisions will provide a higher performing and more accurate analysis of the audio spectrum. The full research and design process for the real-time audio analyser is discussed and both Problems and pitfalls with the final implemented design are highlighted and possible resolutions were investigated. The development costs (excluding labour) are given in the form of a bill of materials (BOM) with the total costs averaging around R1000. Moreover, the additional VGA controller could further decrease the overall costs with the removal of the TFT-LCD screen from the audio analyser and provided the external display was not included in the BOM

Interactive Real-Time Embedded Systems Education Infused with Applied Internet Telephony

The transition from traditional circuit-switched phone systems to modern packet-based Internet telephony networks demands tools to support Voice over Internet Protocol (VoIP) development. In this paper, we introduce the XinuPhone, an integrated hardware/software approach for educating users about VoIP technology on a real-time embedded platform. We propose modular course topics for design-oriented, hands-on laboratory exercises: filter design, timing, serial communications, interrupts and resource budgeting, network transmission, and system benchmarking. Our open-source software platform encourages development and testing of new CODECs alongside existing standards, unlike similar commercial solutions. Furthermore, the supporting hardware features inexpensive, readily available components designed specifically for educational and research users on a limited budget. The XinuPhone is especially good for experimenting with design trade-offs as well as interactions between real-time software and hardware components

Database of audio records

Diplomka a prakticky castDiplome with partical part

Musical notes classification with Neuromorphic Auditory System using FPGA and a Convolutional Spiking Network

In this paper, we explore the capabilities of a sound classification system that combines both a novel FPGA cochlear model implementation and a bio-inspired technique based on a trained convolutional spiking network. The neuromorphic auditory system that is used in this work produces a form of representation that is analogous to the spike outputs of the biological cochlea. The auditory system has been developed using a set of spike-based processing building blocks in the frequency domain. They form a set of band pass filters in the spike-domain that splits the audio information in 128 frequency channels, 64 for each of two audio sources. Address Event Representation (AER) is used to communicate the auditory system with the convolutional spiking network. A layer of convolutional spiking network is developed and trained on a computer with the ability to detect two kinds of sound: artificial pure tones in the presence of white noise and electronic musical notes. After the training process, the presented system is able to distinguish the different sounds in real-time, even in the presence of white noise.Ministerio de Economía y Competitividad TEC2012-37868-C04-0

Access to recorded interviews: A research agenda

Recorded interviews form a rich basis for scholarly inquiry. Examples include oral histories, community memory projects, and interviews conducted for broadcast media. Emerging technologies offer the potential to radically transform the way in which recorded interviews are made accessible, but this vision will demand substantial investments from a broad range of research communities. This article reviews the present state of practice for making recorded interviews available and the state-of-the-art for key component technologies. A large number of important research issues are identified, and from that set of issues, a coherent research agenda is proposed