Tina John University of Munich Workshop on standards for phonological corpora Tina John M.A. 1

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Alexander Miller
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1 Tina John University of Munich 1

2 Emu Speech Database System Database system for: audio data parametrical data annotation 2

3 Emu Speech Database System provides: 3

Platforms following setups are available

3 Solaris (this summer) build it for your

4 Platforms following setups are available Linux Mac OsX (universial build) > 10.3 Windows (not tested much on Windows 7) upcoming builds: Mac OsX < 10.3 Solaris (this summer) build it for your platform using the open source from CVS ( 4

5 Database organisation Emu Speech Database 5

6 Database organisation Emu Speech Database there is a graphical user interface for creating the template content 6

7 Emu Speech Database System Database storage local or on server apart from the EMU Systems Storage of data and access to data organized by the local or server system Database structure defined by limited database template location of signals and annotations structure of annotation display options Database organisation via access to database template and template contents 7

8 Exchange of databases zip your database in a given format create a database information file put both on a server send url of db information file to recipient... 8

9 audio data processed for display and play by The Snack Sound Toolkit supported audio formats: WAV, MP3, AU, SND, AIFF, SD, SMP, CSL processed for data analysis by tkassp a GUI for the assp tools supported audio formats: WAV, AU, SND, AIFF, CSL Emu totally supported audio formats: WAV, AU, SND, AIFF, CSL 9

parametrical data derived from audio data by tkassp stored in the Simple Signal File Format a simple version of the ESPS data file format Header: ASCI

10 parametrical data derived from audio data by tkassp stored in the Simple Signal File Format a simple version of the ESPS data file format Header: ASCI Magic: SSFF (c) SHLRC time information information about postion of included data name, type, nr. of columns 17 - mark end of header Data stored as binary 10

11 annotation different types of annotation: timeless hierarchical times of segments derived from associated segments without any time at all time bounded segments / intervals events / points in time stored in different label files not independent but usable apart from each other unicode utf8 / utf16 not supported yet 11

1 (current) # - marks end of header Data: time in template defined time units segments end time

12 time bounded annotation stored in Emu label files with user defined (in template file) extension in minor modified ESPS xlabel file format ASCI Header (optional): signal utterance name nfields 1 (current) # - marks end of header Data: time in template defined time units segments end time onset time of the first segment is marked by H# events time mark Number a colour code the label 12

13 time less and hierarchical annotation stored in Emu hlb file (extension) hierarchical label files ASCI Magic : ** EMU hierarchical labels** Number of labels Information per level Association of segments encoded by their segment numbers per Segment 13

14 hierarchical label files Information per level Level Labeltype1 Labeltype2... information per segment Segment number # in order of creation label of labeltype1 label of labeltype2... Association of segments per Segment segment number ordered segment numbers of associated labels 14

15 hierarchical label files time bounded not associated labels chronologically ordered totally time less labels 15

16 hierarchical label files.hlb includes: all tiers all labels at all tiers time less and time bounded all associations between labels does not contain any time information but the order of the labels of time bounded levels Usable without external label files but need to be in line with the label files if they are used together 16

17 Interface to other speech proc. tools direct access: Praat wavesurfer ESPS read only: ACCOR, SPEECHSTN, TIMIT, KIEL (simple old format) indirect access: per converting Praat per one way conversion Kiel Corpus Articulate Assistant 17

18 Interface to Praat on the fly conversion of time bounded tiers to Praat TextGrid TextGrid and Sound opened via Sendpraat hierarchical information is kept segment numbers in front of label save changes via praat script tcl script derives changes from the given segment numbers direct access video 18

19 Interface to Praat direct access 19

20 Interface Emu-Praat-Emu conversion of all tiers to Praat TextGrid times of timeless tiers are derived from associated segments absolute time less labels are ignored looses metric of data indirect access 20

21 Interface Emu-Praat-Emu conversion of all Praat tiers to time bounded Emu levels one label file per tier creates corresponding database template file additional information needs to be added to the template indirect access 21

22 Interface Emu-Praat-Emu indirect access 22

23 Interface Emu-Praat-Emu associate segments from time 23

24 Interface to Kiel Corpus per one way conversion Kiel Corpus labelling includes: orthographic canonical differences between canonical and phonetical realisation phonetical autosegmental prosodical stress intonation paralinguistical annotation file Rearrange linear labelling to readable hierarchy 24

25 a Kiel Corpus annotation file 25

26 annotation file 26

27 Different hierarchies 27

28 Query Language use the Emu Query Language to query your annotation structure for everything you annotated Example: 4 syllabic words with word inital /f/ in an L Phrase that occure after a function Word. Query string: [ Word!= g4d6j7 & Func = I -> [ [ Word!= g4d6j7 & Num ( Word,Syllable ) = 4 ^ Phrase = L ] ^ Kanonic = f & Start ( Word,Kanonic ) = 1 ] ] graphical solution to get the query string: 28

29 29

30 Interface to R an example explains more than words 30

31 Vowelspace analysis Vowelspace 31

32 Vowel space analysis in R use R to query the vowels in the database for the male and female speaker query formant values at the mid of segments plot the vowel spaces 32

33 create dictionary of database words use R to query the database for words and the linked phonetic segments order the results write dictionary to Excel readable csv file 33

34 Requests from 1 st workshop day and what Emu can solve: availability of tools on different platforms Win Mac Linux less scripting more Graphical User Interfaces Database/Corpus exchangeability Information about updates of tools via emu.sf.net only yet Alignment of audio and text running on old machines turn taking / conversation overlapping make use of suitable annotation structure (link segments to speaker) Query/ search function for metadata and segmental data (add and link metadata to annotation) Quantitative and qualitative analyses use emu/r functions Visualisation of vowel space use emu/r functions make a dictionary from corpus use emu/r functions interlinear morpheme translation make use of suitable annotation structure (time less linked annotations), may be use auto hierarchy build functions for automatic annotation 34

35 Emu at WWW setup patches documentation publications FAQ mailing list forum feature request bug and feature request tracking system Introduction to the Emu system: Thank You Harrington, J. (in press). Phonetic Analysis of speech corpora. Blackwell. 35

WaveSurfer at a glance

WaveSurfer at a glance WaveSurfer has a simple but powerful interface. The basic document you work with is a sound. When WaveSurfer is first started, it contains an empty sound. You can load a sound file