Emer Gilmartin, Carl Vogel, ADAPT Centre Trinity College Dublin Stitching together the conversation – design considerations for casual talk  Emer Gilmartin, Carl Vogel, ADAPT Centre Trinity College Dublin

Hello Santa Fe I’m really sorry not to be here in person, and hope all are enjoying workshop!

Motivation To better understand the bundle of signals in conversation

SDS technology based on The Problem: Building companion dialogue systems entails understanding of casual dialogue but… Much linguistic theory is based on language similar to writing but highly unlike talk regards spoken interaction as debased, chaotic SDS technology based on Practical Dialogue Hypothesis (Allen, 2000) Constraint introduced to make dialogue modelling tractable Much corpus study of spoken interaction based on Task-based Dialogue Information gap activities – MapTask (HCRC), DiaPix (Lucid) Meetings – AMI, ICSI These are not corpora of casual or social talk The background motivation for this work is to design more human like dialog systems.

Transactional v Interactional Conversation Ordering a pizza (transactional) performing a well-defined task content (‘What?’) vital for success Chat with neighbour (interactional) building/maintaining social bonds social (‘How?’) very important Longer form (c 1 hr) casual conversation ‘continuing state of incipient talk’ Interested in the structure of such conversations

Casual Conversation ‘Unmarked’ central case of spoken interaction A lot of theory and transcript based work, need for multimodal corpus based studies Not monolithic. Can be described at level above the utterance or adjacency paiar as a series of phases: greeting, approach, centre, leavetaking (Ventola) as highly interactive ‘chat’ and more monologic ‘chunk’ phases Often multiparty, variable duration – up to several hours Most existing corpora task-based, existing casual talk corpora dyadic and short duration (5-15 minutes)

Chat and Chunk BOTH FRAMES SHOW 2 MINUTES OF 5-PARTY CONVERSATION – 1 LINE PER PERSON DARK GREEN IS SPEECH, GREY IS SILENCE, YELLOW IS LAUGHTER THE TOP FRAME SHOWS INTERACTIVE CHAT BOTTOM FRAME SHOWS MORE CHUNK-LIKE TALK WITH LONG TURNS BY INDIVIDUAL SPEAKERS – FOR EXAMPLE SPEAKER 3 HAS A CHUNK FOR MOST OF THE MIDDLE OF THIS FRAME

Data – 6 multiparty conversation of around 1 hour each IWSDS 2016 a segment where one speaker takes the floor and is allowed to dominate the conversation for an extended period. The annotations resulted in 213 chat segments and 358 chunk segments

Annotated into chat and chunk All conversations manually segmented at Intonational Phrase (IP) level Manual segmentation was necessary as number of speakers made automatic speaker diarization impossible All conversations transcribed Chunks marked using Slade and Eggins’ definition of chunks –`a segment where one speaker takes the floor and is allowed to dominate the conversation for an extended period.’ All non-chunk conversation considered chat. Guidelines for annotation created to help disambiguate unclear cases.

Chat/Chunk Analysis Analysis of Chat and Chunk Phases January 15, 2016 IWSDS 2016 Analysis of Chat and Chunk Phases Phase length, laughter, overlap contrasted in chat and chunk phases. Generally more chat at conversation beginnings, more time overall spent in chunk phases and more chunk phases in all conversations. Probability of transition from chunk to chat falls as conversation progresses. Phase Duration Mean chunk duration approx. 34s Mean chat duration approx. 28s Chunk duration distribution tighter Distributions significantly different Chunk duration Not speaker , gender, conversation dependent

Laughter More laughter in chat than chunk Median laughter proportions: Chat – 5.4% of production Chunk – 2.2% of production 81% of laughter in chunks non-owners

Chat/Chunk analysis Overlapping Speech More overlap in chat than chunk Median overlap proportions Chunks - 5.7% (mean = 7.3%) Chat - 14.3% (mean = 16%) Floor Occupancy (% time spent) Overlap and silence more common in chat than in chunk phases More than two speakers in overlap rare

Work in Progress: Topic Topic is a feature used to segment text (written or oral) Topic segmentation for casual talk is difficult – shading and shifting Chat/Chunk is distinguishable from speech and silence annotation Could chat/chunk phases correspond to topic boundaries in dialogue? Dataset has been annotated for topic, using ‘aboutness’ Currently working on comparing and contrasting chat/chunk and topic segments in terms of temporal span

Questions? gilmare@tcd.ie Thank You Questions? gilmare@tcd.ie