Proceedings Article10.1109/ECAI.2015.7301172
Monitoring a cloud-based speech processing system
George Suciu,Alexandru Vulpe,Stefan-Ciprian Arseni,Alexandru Stancu,Cristina Butca,Victor Suciu +5 more
- 25 Jun 2015
4
TL;DR: An experimental solution for synthesis and voice recognition which is adapted for use in Romanian language, and integrated with a call center application using the local network and a solution that allows users and providers to reduce the usage of the computational resources by monitoring the systems and services offered by the cloud computing solution.
read more
Abstract: Currently, speech technology is used in various fields, such as: health care, military, telephony, education, aerospace research, telemetry, home automation, etc. This paper describes an experimental solution for synthesis and voice recognition which is adapted for use in Romanian language, and integrated with a call center application using the local network and a solution that allows users and providers to reduce the usage of the computational resources, conforming to the continually changing of business requirements inside an organization, by monitoring the systems and services offered by the cloud computing solution. The purpose of this paper is to propose a prototype communications system which integrates speech technology that makes interaction between customers / citizens and agents of contact center much easier. The main contribution of this paper is to describe the monitoring of a speech processing platform starting from a solution of “call / contact center” and the notification of security alerts by integrating a “text-to-speech” synthesizer in the Romanian language together with a “speech-to-text” application. Finally, the paper examines the main discoveries for a reference application of the monitoring system using the OpenStack cloud platform.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Development and testing of an audio forensic software for enhancing speech signals masked by loud music
Robert Alexandru Dobre,Cristian Negrescu,Dumitru Stanomir +2 more
- 14 Dec 2016
TL;DR: The paper proposes an adaptive filters based solution to remove the musical content from a previously described signal mixture in order to recover the masked vocal signal.
4
Investigation on speech recognition Accuracy via Sphinx toolkits
03 Mar 2022
TL;DR: In this article , the authors evaluated the Sphinx open-source speech recognition toolkit in terms of usability and expense of recognition accuracy using Amazigh language and found that the best recognition rate was recorded by Pocketsphinx toolkit.
2
Analysis of Network Management and Monitoring Using Cloud Computing
George Suciu,Victor Suciu,Razvan Gheorghe,Ciprian Dobre,Florin Pop,Aniello Castiglione +5 more
- 21 Nov 2015
TL;DR: An integrated solution that is deployed in the cloud for monitoring all the network components, allowing administrator to verify connectivity of the equipment, their performances and network security.
1
Automatic Speech Recognition Analysis Over Wireless Networks
Diana Birchall
- 01 Jan 2023
TL;DR: In this article , the effects on speech recognition performance by the speech coders are presented, and the results show that the best performance is 84.14% achieved by using the GSM audio codec, while the VoIP codec used in this work are G.711, GSM and Speex depending on the SIP protocol.
1
References
Making Machines Understand Us in Reverberant Rooms: Robustness Against Reverberation for Automatic Speech Recognition
Takuya Yoshioka,Armin Sehr,Marc Delcroix,Keisuke Kinoshita,Roland Maas,Tomohiro Nakatani,Walter Kellermann +6 more
TL;DR: For a number of unexplored but important applications, distant microphones are a prerequisite for extending the availability of speech recognizers as well as enhancing the convenience of existing speech recognition applications.
Enhanced Monitoring-as-a-Service for Effective Cloud Management
Shicong Meng,Ling Liu +1 more
TL;DR: This paper presents three enhanced MaaS capabilities and shows that window- based state monitoring is not only more resilient to noises and outliers, but also saves considerable communication cost and violation-likelihood-based state monitoring can dynamically adjust monitoring intensity based on the likelihood of detecting important events, leading to significant gain in monitoring service consolidation.
106
Cloud Application Monitoring: The mOSAIC Approach
Massimiliano Rak,Salvatore Venticinque,Tam´s M´hr,Gorka Echevarria,Gorka Esnal +4 more
- 29 Nov 2011
TL;DR: The mOSAIC monitoring components that facilitate the building of custom monitoring systems for cloud applications using the m OSAIC API are introduced.
84
Model-Based Approaches to Handling Uncertainty
M. J. F. Gales
- 01 Jan 2011
TL;DR: This chapter describes the underlying concepts of model-based noise compensation for robust speech recognition and how it can be applied to standard systems and considers important practical issues.
Free-text data entry by speech recognition software and its impact on clinical routine.
TL;DR: An increase in productivity compared with that of conventional transcription was found at an error rate of less than 16%, and best results were obtained with the specialty-related vocabulary database added by the analysis of the authors' own documents.
16