SEMAINE-1.0 speech to speech dialog system

Pre-condition for all demonstrator configurations

Start an ActiveMQ server.

If you intend to run the demonstrator distributed across several machines, read Running a distributed system.

Text input, speech output

The simplest configuration of the system is a pure java system in which the user types his/her input via a GUI window, and hears the system response via speech output.

This system configuration pre-supposes installation of SEMAINE-1.0-java.

The system can be started as follows.

  • on Linux/Mac/Unix:
  • on Windows:

Speech input, speech output

In this configuration, the user speaks to the system through a microphone, and the system response is produced via speech output.

This system configuration pre-supposes installation of SEMAINE-1.0-java and SEMAINE-1.0-linux.

The system can be started as follows.

1. Start the Java component

  • on Linux/Mac/Unix:

2. Start the Linux components

Make sure you have compiled the linux code.

The minimal Linux component to start is the SMILE component, doing feature extraction, voice activity detection, and emotion/interest recognition. Start it as:


In addition, it is advisable to start the Automatic Speech Recognition (ASR) component, so that the system has a chance to understand what the user is saying. (Note that the quality of ASR output at this stage is extremely limited due to very preliminary training data.)


Testing microphone level

It is essential for the proper functioning of the SMILE component that the microphone recording level is set to a reasonable value. To test that, watch the shell from which you started the SMILE component. When you start talking, the SMILE component should output a message saying "detected turn start", and when you stop talking, it should output a message saying "detected turn end". If there are no "turn start" messages, increase the recording volume; if there are no "turn end" messages, decrease the recording volume.

Last modified 9 years ago Last modified on 01/05/09 15:30:58