A traditional pipeline model for a spoken language dialogue system includes the following components: 1. Speech Input: The system takes in spoken language input from the user through a microphone or other input device. 2. Speech Recognition: The input speech is converted into text using automatic speech recognition (ASR) technology. 3. Natural Language Understanding: The text is analyzed and interpreted to extract the meaning and intent of the user's input. 4. Dialogue Management: The system determines an appropriate response based on the user's input, taking into account context, previous dialogue turns, and system goals. 5. Natural Language Generation: The response is generated in natural language to be communicated back to the user. 6. Speech Synthesis: The generated text response is converted back into spoken language using text-to-speech (TTS) technology. 7. Speech Output: The synthesized speech is played back to the user through a speaker or other output device. Traditionally, these components are implemented separately using different technologies and underlying models. This model allows the integration of existing systems for each component, for example, ASR and TTS systems. In an [[end-to-end model]] these components are merged into a single model.