1. A system having a client-server architecture for Automatic Speech Recognition (ASR) applications, comprising: a) client-side including: a.1) a client being part of distributed front end for converting acoustic waves to feature vectors representing the properties of said acoustic waves using Digital Signal Processing (DSP); a.2) Voice Activity Detection for separating between speech and non-speech acoustic signals and for environmental compensation; a.3) adaptor for WebSockets to pipeline chunked feature vectors to the server side; b) a server side including: b.1) A web layer utilizing HTTP protocols and including a Web Server having a Servlet Container which contains dedicated servlet for managing voice recognition sessions that include transferring WebSockets' packets to messages and returning responses and diagnostic message to client, said layer being an access point for corporate information systems, and a point of integration with another web application, which are used for load balancing and. authentication and authorization of clients; b.2) an intermediate layer for transport based on Message-Oriented Middleware (MOM) being a message broker, to which all other server parts are connected, for feature vector streaming, for communication and integration, and for load balancing between said client side and said server side; b.3) a recognition server and an adaptation server both connected to said intermediate layer, said adaptation server being connected via an adaptation channel, said recognition server interacts with said client side via a recognition channel and a Distributed Frontend (DFE); b.4) a Speech processing server consisting of a server part of distributed front end, a Recognition Server and an Adaptation Server; b.5) a Recognition Server for instantiation of a recognition channel per client; b.6)an Adaptation Server for adaptation acoustic and linguistic models for each speaker; b.7) a Bidirectional communication channel between Speech processing server and client side via distributed frontend said recognition channel; and b.8) a Persistent layer for storing, a Language Knowledge Base connected to said Speech processing server, and includes a dictionary, acoustic models, statistical language models and language patterns.
1. A system having a client-server architecture for Automatic Speech Recognition (ASR) applications, comprising: a) client-side including: a.1) a client being part of distributed front end for converting acoustic waves to feature vectors representing the properties of said acoustic waves using Digital Signal Processing (DSP); a.2) Voice Activity Detection for separating between speech and non-speech acoustic signals and for environmental compensation; a.3) adaptor for WebSockets to pipeline chunked feature vectors to the server side; b) a server side including: b.1) A web layer utilizing HTTP protocols and including a Web Server having a Servlet Container which contains dedicated servlet for managing voice recognition sessions that include transferring WebSockets' packets to messages and returning responses and diagnostic message to client, said layer being an access point for corporate information systems, and a point of integration with another web application, which are used for load balancing and. authentication and authorization of clients; b.2) an intermediate layer for transport based on Message-Oriented Middleware (MOM) being a message broker, to which all other server parts are connected, for feature vector streaming, for communication and integration, and for load balancing between said client side and said server side; b.3) a recognition server and an adaptation server both connected to said intermediate layer, said adaptation server being connected via an adaptation channel, said recognition server interacts with said client side via a recognition channel and a Distributed Frontend (DFE); b.4) a Speech processing server consisting of a server part of distributed front end, a Recognition Server and an Adaptation Server; b.5) a Recognition Server for instantiation of a recognition channel per client; b.6)an Adaptation Server for adaptation acoustic and linguistic models for each speaker; b.7) a Bidirectional communication channel between Speech processing server and client side via distributed frontend said recognition channel; and b.8) a Persistent layer for storing, a Language Knowledge Base connected to said Speech processing server, and includes a dictionary, acoustic models, statistical language models and language patterns. 3. A system according to claim 1 , in which the DFE comprises: a) a DSP module for preprocessing and conversion of audio data to feature vectors; b) VAD filters; c) web protocol input/output adaptors and message queue producer/consumer adaptor on the server side, for encapsulating complexities of dedicated transport marshaling and unmarshaling.