The adaptive multirate wideband speech codec (AMR-WB)

Bessette, B.; Salami, R.; Lefebvre, Rémi; Jelinek, Milan; Rotola-Pukkila, J.; Vainio, J.; Mikkola, H.; Järvinen, Kari

doi:10.1109/tsa.2002.804299

Cited by 255 publications

(160 citation statements)

References 6 publications

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“…Voice is encoded in mobile phone networks using adaptive multirate (AMR) codecs. In GSM and wCDMA, a narrowband AMR scheme is used and with a typical data rate of 12.2 kbps [6]. A higher quality wideband AMR is used in LTE and offers superior quality at a data range of 12.5 kbps [6,7].…”

Section: IIImentioning

confidence: 99%

Towards a Quantitative Model of Mobile Phone Usage Ireland - a Preliminary Study

Farrell

Carolan

McLoone

et al. 2012

IET Irish Signals and Systems Conference (ISSC 2012)

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Abstract-Mobile phone networks were traditionally voice and SMS messaging networks which made them easy to quantify and model. More recently with the advent of broadband data connections and smart phones, mobile phone networks are being used for a wide range of purposes using ever more bandwidth. This paper utilises data provided by an Irish operator to provide an initial perspective on the current uses of mobile phone networks as a within Ireland. This work serves as a precursor to the development of a quantitative model of existing behaviour which in turn will help predict future requirements.

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Section: IIImentioning

confidence: 99%

Towards a Quantitative Model of Mobile Phone Usage Ireland - a Preliminary Study

Farrell

Carolan

McLoone

et al. 2012

IET Irish Signals and Systems Conference (ISSC 2012)

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“…The LPC technique is widely used in speech coding, e.g., in GSM 06. 10 [11] or in narrow-band and wide-band adaptive multi-rate coders (AMR) [6]. It can also be used to parametrize signals in speech or speaker recognition.…”

Section: Linear Prediction Theorymentioning

confidence: 99%

Increasing anti-spoofing protection in speaker verification using linear prediction

Janicki

2016

Multimed Tools Appl

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This article addresses the problem of anti-spoofing protection in an automatic speaker verification (ASV) system. An improved version of a previously proposed spoofing countermeasure is presented. The presented method is based on the analysis of linear prediction error that results from both short-and long-term prediction of the input speech signal. It was observed that non-natural speech signals, i.e., synthetic or converted speech, were predicted in a different way than genuine speech. Therefore, in contrast to the classical linear prediction analysis, where usually only the prediction coefficients are analyzed, in the proposed approach the residual (error) signals were examined. During this analysis, 23 various prediction parameters were extracted, such as the energy of the prediction error, prediction gains and temporal parameters related to the prediction error signals. Various binary classifiers were researched to separate human and spoof classes, however the support vector machines with radial basis function (SVM-RBF) yielded the best results. When tested on the corpora provided for the ASVspoof 2015 Challenge, the proposed countermeasure returned better results than the previous version of the algorithm and, in most of the cases, the baseline spoofing detector based on the local binary patterns (LBP). It is hoped that the proposed method can be part of a generalized spoofing countermeasure helping to increase security of ASV systems.The calculations described in the article were made in the Interdisciplinary Centre for Mathematical and Computational Modelling (ICM) of the University of Warsaw (computational grant No. G46-2).

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“…Voice is encoded in mobile phone networks using adaptive multi-rate (AMR) codecs. In GSM and wCDMA, a narrowband AMR scheme is used with a typical data rate of 12.2 kbps [13]. A higher quality wideband AMR is used in LTE and offers superior quality at a data range of 12.5 kbps [13,14].…”

Section: A) Expressing the Data And Identifying Smartphone Subscribersmentioning

confidence: 99%

“…In GSM and wCDMA, a narrowband AMR scheme is used with a typical data rate of 12.2 kbps [13]. A higher quality wideband AMR is used in LTE and offers superior quality at a data range of 12.5 kbps [13,14]. Higher and lower data rates are possible, but for this paper a rate of 12.5 kbps will be used in converting voice channels to an equivalent data session.…”

Section: A) Expressing the Data And Identifying Smartphone Subscribersmentioning

confidence: 99%

Comparing and Contrasting Smartphone and Non-Smartphone Usage

Carolan

McLoone

Farrell

2013

24th IET Irish Signals and Systems Conference (ISSC 2013)

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_______________________________________________________________________________Abstract-This paper presents a large-scale network wide analysis of both user behaviour and network dynamics in a live nationwide 2G/3G network. The employed data set tracks over one million subscribers across upwards of ten thousand base stations covering the entirety of the Republic of Ireland. The data set was captured in 2011 and includes a large group of bill-pay and pre-pay smartphone subscribers. The proliferation of smartphones has been a major and recent change to networks worldwide. In light of the recent changes in network access technologies much of the earlier work in this field is now out of date. This paper compares and contrasts the traffic usage of smartphone subscribers and nonsmartphone subscribers. A key aim of this work is to quantify and qualify the change brought about by smartphones. Unlike previous studies, we look to the future by treating all traffic including voice calls and SMS as an equivalent data service, as will be the case in 4G. This paper also explores the temporal and spatial properties of both bill-pay and pre-pay smartphone usage and concludes by summarising our key findings & their implications.

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The adaptive multirate wideband speech codec (AMR-WB)

Cited by 255 publications

References 6 publications

Towards a Quantitative Model of Mobile Phone Usage Ireland - a Preliminary Study

Towards a Quantitative Model of Mobile Phone Usage Ireland - a Preliminary Study

Increasing anti-spoofing protection in speaker verification using linear prediction

Comparing and Contrasting Smartphone and Non-Smartphone Usage

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