iai-group · NoB0 · May 7, 2024 · Feb 21, 2024 · Feb 22, 2024 · Feb 26, 2024
diff --git a/README.md b/README.md
@@ -38,7 +38,7 @@ Below is the overview of IAI MovieBot 2.0 architecture. Blue components are inhe
     - Telegram
     - Flask REST
     - Flask socket.io
-  * Natural Language Understanding (NLU)
+  * Natural Language Understanding (NLU) [[doc](https://iai-moviebot.readthedocs.io/en/latest/nlu.html)]
     - Rule-based
     - JointBERT
   * Dialogue management

diff --git a/docs/source/architecture.rst b/docs/source/architecture.rst
@@ -3,16 +3,15 @@ System Architecture
 
 This page provides a high-level overview of the architecture of our system.  At this level of abstraction, our system constitutes a domain-independent framework for facilitating conversational item recommendation.  Thus, even though we will be using movie-related examples for illustration, it is straightforward to adapt the system to other domains.
 
-The system architecture is shown in the figure below, illustrating the core process for each dialogue turn.
+The overview of the system architecture is shown in the figure below.
 
-.. image:: _static/Blueprint_MovieBot.png
+.. image:: _static/Blueprint_MovieBot_v2.png
 
+The main components of the system are:
 
-Natural Language Understanding
-------------------------------
-
-The :py:class:`NLU <moviebot.nlu.nlu>` component converts the natural language :py:class:`UserUtterance <moviebot.core.utterance.utterance.UserUtterance>` into a :py:class:`DialogueAct <moviebot.dialogue_manager.dialogue_act>`. This process, comprising of *intent detection* and *slot filling*, is performed based on the current dialogue state.
-
+- :doc:`Natural Language Understanding <nlu>`
+- Dialogue Manager
+- Natural Language Generation
 
 Dialogue Manager
 ----------------

diff --git a/docs/source/contact.rst b/docs/source/contact.rst
diff --git a/docs/source/dialogue.rst b/docs/source/dialogue.rst
@@ -16,31 +16,7 @@ User intents
 
 :py:class:`UserIntents <moviebot.intents.user_intents>`
 
-+------------------------+------------+
-| Intent   | Description   |
-+========================+============+
-| Reveal   | The user wants to reveal a preference.   | 
-+------------------------+------------+
-| Inquire  | Once the agent has recommended an item, the user can ask further details about it.        | 
-+------------------------+------------+
-| Remove preference  | The user wants to remove any previously stated preference.        | 
-+------------------------+------------+
-| Reject  | The user either has already seen/consumed the recommended item or does not like it.        | 
-+------------------------+------------+
-| Accept  | The user accepts (likes) the recommendation. This will determine the success of the system as being able to find a recommendation the user liked.        | 
-+------------------------+------------+
-| Continue recommendation  | If the user likes a recommendation, they can either restart, quit or continue the process to get a similar recommendation.        | 
-+------------------------+------------+
-| Restart  | The user wants to restart the recommendation process.        | 
-+------------------------+------------+
-| Acknowledge  | Acknowledge the agent's question where required.        | 
-+------------------------+------------+
-| Deny  | Negate the agent's question where required.        | 
-+------------------------+------------+
-| Hi  | When the user initiates the conversation, they start with a formal hi/hello or reveal preferences.        | 
-+------------------------+------------+
-| Bye  | End the conversation by sending a bye message or an exit command.        | 
-+------------------------+------------+
+A detailed description is provided :doc:`here <nlu>`.
 
 Agent intents
 """""""""""""

diff --git a/docs/source/index.rst b/docs/source/index.rst
@@ -13,7 +13,6 @@ The distinctive features of IAI MovieBot include a task-specific dialogue flow,
    architecture
    dialogue
    reinforcement_learning
-   contact
 
 
 Indices and tables

diff --git a/docs/source/nlu.rst b/docs/source/nlu.rst
@@ -0,0 +1,64 @@
+Natural Language Understanding
+------------------------------
+
+The natural language understanding (NLU) component converts incoming user utterances into dialogue acts.
+A dialogue act is a structured representation comprising an intent and parameters. A parameter is a triplet including a slot, an operator, and a value. Note that the user intents and slots, that are domain specific, are pre-defined and can easily be modified to fit a new domain.
+The NLU process is divided into two steps: intent classification and slot filling.
+
+Two types of NLU component are available:
+
+- :py:class:`RuleBasedNLU <moviebot.nlu.rule_based_nlu.RuleBasedNLU>`: intents and parameters are extracted using pre-defined rules.
+- :py:class:`NeuralNLU <moviebot.nlu.neural_nlu.NeuralNLU>`: intents and parameters are extracted using a JointBERT model with a CRF layer [1]_. Training data and scripts are released with the code.
+
+User Intents
+------------
+
+:py:class:`UserIntents <moviebot.intents.user_intents>`
+
++--------------------------+----------------------------------------------+
+| Intent                   | Description                                  |
++==========================+==============================================+
+| Reveal                   | The user wants to reveal a preference.       |
++--------------------------+----------------------------------------------+
+| Inquire                  | Once the agent has recommended an item,      |
+|                          | the user can ask further details about it.   |
++--------------------------+----------------------------------------------+
+| Remove preference        | The user wants to remove any previously      |
+|                          | stated preference.                           |
++--------------------------+----------------------------------------------+
+| Reject                   | The user either has already seen/consumed    |
+|                          | the recommended item or does not like it.    |
++--------------------------+----------------------------------------------+
+| Accept                   | The user accepts (likes) the recommendation. |
+|                          | This will determine the success of the system|
+|                          | as being able to find a satisfying           |
+|                          | recommendation.                              |
++--------------------------+----------------------------------------------+
+| Continue recommendation  | If the user likes a recommendation, they can |
+|                          | either restart, quit, or continue the process|
+|                          | to get a similar recommendation.             |
++--------------------------+----------------------------------------------+
+| Restart                  | The user wants to restart the recommendation |
+|                          | process.                                     |
++--------------------------+----------------------------------------------+
+| Acknowledge              | Acknowledge the agent's question where       |
+|                          | required.                                    |
++--------------------------+----------------------------------------------+
+| Deny                     | Negate the agent's question where required.  |
++--------------------------+----------------------------------------------+
+| Hi                       | When the user initiates the conversation,    |
+|                          | they start with a formal hi/hello or reveal  |
+|                          | preferences.                                 |
++--------------------------+----------------------------------------------+
+| Bye                      | End the conversation by sending a bye message|
+|                          | or an exit command.                          |
++--------------------------+----------------------------------------------+
+
+Slots
+-----
+
+The slots are defined in the enumeration :py:class:`Slots <moviebot.nlu.annotation.slots.Slots>`. Note that some of these slots cannot be filled upon the reception of a user utterance, such as `imdb_link` and `cover_image`. 
+
+**References**
+
+.. [1] Chen, Q., Zhuo, Z., & Wang, W. (2019). BERT for Joint Intent Classification and Slot Filling. arXiv preprint arXiv:1902.10909.