Audio Signal Processing

A recent neuro-spiking coding scheme for feature
extraction from biosonar echoes of various plants is examined with a
variety of stochastic classifiers. Feature vectors derived are employed
in well-known stochastic classifiers, including nearest-neighborhood,
single Gaussian and a Gaussian mixture with EM optimization.
Classifiers’ performances are evaluated by using cross-validation and bootstrapping techniques. It is shown that the various classifiers perform equivalently and that the modified preprocessing configuration yields considerably improved results.

An improved processing description to be employed
in biosonar signal processing in a cochlea model is proposed and
examined. It is compared to conventional models using a modified
discrimination analysis and both are tested. Their performances are
evaluated with echo data captured from natural targets (trees).
Results indicate that the phase characteristics of low-pass filters
employed in the echo processing have a significant effect on class
separability for this data.

Per il settore forense, le analisi audio sono un ambito scientifico ancora in piena espansione ed estremamente frammentato. Nonostante ciò, esso racchiude grandissime potenzialità, non soltanto per quanto concerne la voce umana, evidente portatrice di indizi e significante, ma anche per l’estrapolazione di tutti quei particolari sonori utili per l’indagine quali il colpo di pistola (di conseguenza la tipologia di arma), il contesto ambientale, il tipo di autovettura, il sesso del parlatore, eccetera. Durante l’incontro verranno esposte le principali modalità di analisi digitale delle registrazioni tramite esempi e casi reali inerenti temi quali: il riconoscimento del parlatore, la verifica dell’integrità del materiale audio o il problema dell’interpretazione soggettiva del contenuto vocale in presenza di forti disturbi ambientali (quali radio, traffico automobilistico, pioggia, eccetera). L’intercettazione del resto, sia essa telefonica o di altra tipologia, è uno strumento fondamentale per l’indagine preliminare o l’impianto accusatorio e difensivo, ma nel contempo rappresenta un materiale delicato, che necessita l’utilizzo di corrette metodologie di analisi. Dato un quesito, la scienza in tale campo non fornisce ancora certezze probatorie, bensì indizi a favore o sfavore. � invece purtroppo molto più facile creare un danno irreparabile per la società quando l’eventuale prova sia stata analizzata in maniera errata. Questo concetto sarà esplicitato tramite l’esempio di un caso reale (la revisione di una sentenza di condanna) per fornire un ulteriore strumento di difesa da analisi basate su metodi scientificamente non corretti.
I destinatari

Tecnici informatici, manager d’azienda, amministratori di rete, autorità giudiziarie, inquirenti, avvocati, periti informatici, consulenti e altre persone attive nel settore tecnico/giuridico interessate alle attività che riguardano l'informatica forense.

For an improved neuro-spike representation of auditory signals within
cochlea models, a new digital ARMA-type low-pass ¯lter structure is proposed.
It is compared to more conventional AR-type counterpart on a classi¯cation of
biosonar echoes, in which echoes from various tree species insoni¯ed with a bat-like
chirp call are converted to biologically plausible feature vectors. Next, paramet-
ric and non-parametric models of the class-conditional densities are built from the
echo feature vectors. The models are deployed in single-shot and sequential-decision
classi¯cation algorithms. The results indicate that the proposed ARMA ¯lter struc-
ture o®ers an improved single-echo classi¯cation performance, which leads to faster
sequential-decision making than its AR-type counterpart.

Cuando hablamos de desplazamiento del eje de cero absoluto, nos referimos al fenoÌ?meno que en ingleÌ?s es comuÌ?nmente conocido como DC offset, que refiere a un error presente en algunas senÌ?ales de audio, manifiesto por las desigualdades que tenga la misma, en los dominios positivos y negativos con respecto al eje X, al que en este artiÌ?culo preferimos llamar eje de cero absoluto.
Este desplazamiento, seguÌ?n el caso, puede tener muchas variantes. Puede ser uniforme en toda la senÌ?al, como tambieÌ?n puede estar presente en una o maÌ?s secciones. Si la senÌ?al es esteÌ?reo, puede encontrarse en solo un canal, en ambos por igual, o incluso puede estar presente en ambos canales pero con distintos niveles.
En este artiÌ?culo trataremos al desplazamiento del eje desde su geÌ?nesis, identificando sus causas, las problemaÌ?ticas que acarrea y proponiendo una metodologiÌ?a para removerlo satisfactoriamente de una onda de audio.

This article addresses the cultural and historical significance of the modern interpretation of extended range guitars while also discussing specifications of the instruments and the context of a mix. The extended range guitar refers to the added strings on a traditional six string guitar by adding a seventh, eight, and even ninth string to the electric guitar. First, this article explores how artists such as Steve Vai, Korn, Meshuggah, and Animals As Leaders have impacted and shaped the commercial creation, success, and cultural effects on the musical community with these extended range guitars, specifically within heavy metal. Secondly, it examines the specifications of the extended range guitars, such as scale length, string gauges, hardware, wood, and price in relation to seventh, eighth, and ninth strings. Lastly, it discusses how to approach a mix with extended range instruments, considering that these guitars are now interfering with low frequencies in relation to a drum kit and bass guitar.

This Report expresses an integral functionality description of a new Digital Sensor Board called SAVANT node, giving the main theoretical background, of the specific algorithms, data and criteria that I took into account to de- velop a WSN platform. The global design of the SAVANT node is based on the humans symptoms of SAVANT syndrome [1]. The WSN (Wireless Sensor Network) environment evokes the use of a homogeneous network structure, the inclusion of a new special node with a more powerful com- putational resources which could change this network’s dynamic (commonly WSN)

Since Barry Truax’s early pioneering work, the increasing availability of powerful and inexpensive desktop computers has led many composers, researchers and artists to experiment and work with granular synthesis and/or granulation processes. During the last two decades a stream of granulation software has appeared, but despite this spread, all these applications have important limitations in terms of efficiency, usability, flexibility and control. This paper describes an abstraction of an efficient and flexible granular processing system built into the Max/MSP environment.

In this work, we are concerned by a new iterative Kalman filtering scheme where a linear predictor model parameters are estimated from noisy speech. However, when only noise-corrupted speech is available, the enhancement performance of the Kalman filter is somewhat dependent on the accuracy of the linear prediction coefficients (LPCs) and excitation variance estimates. Nevertheless, linear prediction based speech (LPC) analysis is known to be sensitive to the presence of additive noise. To overcome this problem we present in this paper an analysis and application of the LPC-based formant enhancement method by modifying the log magnitude spectrum of the LPC model and then re-evaluating new LPCs to be apply on the Kalman filter. These enhanced LPCs are useful indicator of Kalman filter performance. Our enhancement experiments use a NOIZEUS speech corpus where the proposed method achieves higher objective and subjective results compared with other enhancement methods.