DTMF and CLIP decoding in a noisy area using adaptive approach

Multi-frequency signals are greatly used in telecommunication fields. Signaling and speech are such an example of multi-frequency signals exchanging through the telecommunication networks. Extracting the frequencies embedded in these signals is very useful for a lot of operations: like filtering, decoding, compressing….We propose in this paper adaptive technique to process in real time multi-frequency signals and extracting the frequencies that they contain. Keywords: DTMF, CLIP, Noise, Adaptive, Real Tim

Dual Tone Multi Frequency (DTMF) signal generation and detection using MATLAB software

In this study, Dual Tone Multi Frequency (DTMF) signal generation and detection is implemented by using Goertzel Algorithm in MATLAB software. The DTMF signals are generated by using Cool Edit Pro Version 2.0 program for DTMF tone detection. The DTMF signal generation and detection algorithm are based on International Telecommunication Union (ITU) recommendations. Frequency deviation, twist, energy and time duration tests are performed on the DTMF signals. The algorithm recognizes the DTMF tones if they satisfy the recommendations, otherwise they are rejected

ACQR: Acoustic Quick Response Codes for Content Sharing on Low End Phones with No Internet Connectivity.

ABSTRACT In this paper we introduce Acoustic Quick Response codes to facilitate sharing between Interactive Voice Response (IVR) service users. IVRs are telephone-based, and similar to the world wide web in many aspects, but currently lack support for content sharing. Our approach uses 'audio codes' to let people share their call positions, and allows callers to hold their normal (low-end) handsets together to synchronise. The technique uses remote generation and recognition of audio codes to ensure that sharing is possible on any type of phone without the need for textual literacy or an internet connection. We begin by exploring existing user needs for sharing, then evaluate the technical robustness of our audio-based design. We demonstrate the value of the approach for voice service users over several separate studies-including an eight-month extended field deployment-then conclude with a discussion of future possibilities for such scenarios