• research


Maharani: An Open-Source Python Toolkit for ISU Dialogue Management

Based on the previous TrindiKit implementation of the ISU approach to dialogue management (which used a proprietary Prolog), we are now developing Maharani, an open-source Python-based ISU dialogue manager together with Talkamatic AB. The first release is expected in the spring of 2012.

Funding: DTL internal

Researchers: Staffan Larsson, Sebastian Berlin

Reliable Dialogue Annotation for the DICO Corpus

Our purpose is to annotate seven pragmatic categories in the DICO (Villing and Larsson, 2006) corpus of spoken language in an in-vehicle environment, in order to find out more about the distribution of these categories and how they correlate. Some of the annotations have already been made, by one annotator.

To strengthen the results from this work, we are interested in establishing the degree of inter-coder reliability for the annotations. Also, as far as we know, no attempts have been made to annotate enthymemes (Breitholtz and Villing, 2008), a type of defeasible arguments, in spoken dialogue. A corpus of spoken discourse annotated for enthymemes would therefore be a welcome addition to the resources that are currently available.

Researchers: Jessica Villing, Ellen Breitholtz, Staffan Larsson (supervisor)

Funding: CLT internal

End-of-utterance detection

The current dialogue system used at the Dialogue Lab, GoDiS, depends on cut-off values to control turn-taking. This means that when the user has not spoken for a period of time, the system assumes the user is finished and takes the turn. This can lead to both interruptions and unnecessary long waits for the user.

To solve this problem, the system has to be able to detect when a speaker is finished or when he is just making a pause within his utterance. If the system can reliably detect the users end-of-utterance, it can take the turn more rapidly when the user is finished (and avoid interrupting the user when he/she is not finished).

To detect end of utterance, we assume that the system needs information from several sources: syntactic information, prosodic information and also information state. We will create a statistical language model for end-of-utterance detection, using machine learning. For this we will use the Weka toolkit.

We will attempt to create a model that allows the system to differentiate between user pauses within an utterance, and user pauses at the end of an utterance.

Funding: CLT internal.

Duration: August 2011 - October 2012

Researchers: Kristina Lundholm Fors, Staffan Larsson (supervisor).


SIMSI - Safe In-vehicle Multimodal Speech Interfaces

External project site

Driver distraction is a common cause of accidents, and is often in turn caused by the driver interacting with technologies such as mobile phones, media players or navigation systems. A Multimodal HMI system complements traditional human-machine interaction modalities (visual output and haptic input) with spoken interaction. Speech solutions generally aim to increase safety but immature solutions may end up distracting the driver and decreasing safety.

In the SIMSI project, we  aim to integrate an existing safety-oriented multimodal HMI system based on academic research into a commercial-grade HMI platform and uses this integrated system for research on dialogue strategies for cognitive load management and integrated multimodality. We expect to achieve an HMI solution which can be reliably shown to increase safety by reducing distraction, cognitive load and head-down time considerably when compared to other state-of-the-art in-vehicle interaction models. The HMI will be evaluated in simulators and real traffic.

Funding agency: Vinnova (FFI programme)

Partners: Talkamatic AB, Mecel AB

Contact person at CLT: Staffan Larsson

CLT Cloud (A small CLT Project)

SALDO - a Swedish BLARK component

Grammatical Framework (GF)

GF is a multilingual grammar formalism, which is used for building applications such as translators and dialogue systems. GF comes with an extensive resource grammar library for over 10 languages.


Extract is a tool for extraction of linguistic information from raw text data.

BNF Converter

The BNF Converter is a compiler construction tool generating a compiler front-end from a Labelled BNF grammar. It is currently able to generate C, C++, C#, F#, Haskell, Java, and OCaml, as well as XML representations.

Functional Morphology

Functional Morphology is a tool for lexical resource development.