User:Angeliki/Ttssr-Speech Recognition Iterations

Angeliki's collection of texts From Tedious Tasks to Liberating Orality- Practices of the Excluded on Sharing Knowledge, refers to orality in relation to programming, as a way of sharing knowledge including our individually embodied position and voice. The emphasis on the role of personal positioning is often supported by feminist theorists. Similarly, and in contrast to scanning, reading out loud is a way of distributing knowledge in a shared space with other people, and this is the core principle behind the ttssr-> Reading and speech recognition in loop software. Using speech recognition software and python scripts Angeliki proposes to the audience to participate in a system that highlights how each voice bears the personal story of an individual. In this case the involvement of a machine provides another layer of reflection of the reading process. The oral cultures, in contrast to the literate cultures use different methods for maintaining their stories. The two ingredients are the embodied presence of the poet and the oral speech. And at the same time maintaining doesn't seem to be their main purpose, as long as it doesn't satisfy the present audience or oral poet. Although they try to narrate and copy the story of another poet, the way they produce knowledge is fundamentally different. The oral narratives are based on the previous ones keeping a movable line to the past by adjusting to the history of the performer, but only if they are important for the present. From weaving to typewriting and programming women, mainly hidden from the public, were exploring the realm of writing beyond its conventional form. According to Kittler (1999, pg. 221) “A desexualized writing profession, distant from any authorship, only empowers the domain of text processing. That is why so many novels written by recent women writers are endless feedback loops making secretaries into writers”. But aren’t these endless feedback loops similar to the rhythmic narratives of the anonymous oral cultures? How this knowledge is produced through repetitive formulas that are easily memorized? The orality is not built on written practices and texts, but in memory, sounds and human interaction. Oral cultures exist without the need of writing, texts and dictionaries. It doesn’ t need a library to be stored, for people to look up and create their texts. The learning process is shared from individual positions but with the need of the community and is flexible and active to the present.

In the context of the present available technologies (speech recognition, computerised recitation) I am using the errors of these functions to create an new oral experience. As these projects do while following the media of their time. Following the example of two other projects: Boomerang (1974) and I Am Sitting In A Room (1981). The first one is about forming a tape by recording and broadcasting continuously a voice speaking. The latter is exploiting the imperfections of the system of recording tapes machine and grabs the room echoes/as musical qualities in the process (echoes of the room while recording)...tape-delay system/for voice and electromagnetic tape.

This repetition , Boomerang, sitting, typewriters
Participatory
Orality reading/oral poets perform
Scanning/ transcription- history of it and typewriters
formula-instructions

• Description: The first line of a given scanned text is read by someone. Then, the outcome (a sound file) is transcribed by a program, called pocketsphinx, and stored as a textfile. The new line is read by the same person or someone else, whose voice is going to be transcribed. The process is looped 10 times. More specifically every time the previous outcome becomes input for somebody to read and then the transcription follows. Depending on the quality of the machine, the voice and the reading, the first line is being transformed into different texts but with similar phonemes. At the same time with the transcription, each voice is played and repeated for five times, so for some moments they are overlapping each other. The process resembles the game of the broken telephone and the karaoke.
  
• Instructions:

The first line of a scanned text is being projected on the screen. I am reading this line. Pocketsphinx is transcribing my voice, being played in loop for five times. The new line is being projected on the screen. I am passing the microphone to you. While you are reading my transcribed line, you are listening to my voice. Pocketsphinx is transcribing your voice, being played in loop for five times. The new line is being projected on the screen. You are passing the microphone to the next you. While the next you is reading your transcribed line, is listening to your voice. Pocketsphinx is transcribing the voice of the next you, being played in loop for five times. The new line is being projected on the screen. The next you is passing the microphone to the next next you. While the next next you is reading the transcribed line of the next you, is listening to the voice of the next you. Pocketsphinx is transcribing the voice of the next next you, being played in loop for five times. The new line is being projected on the screen. The next next you is passing the microphone to the next next next you. While the next next next you is reading the transcribed line of the next next you, is listening to the voice of the next next you. Pocketsphinx is transcribing the voice of the next next next you, being played in loop for five times. The process continuous for five more times. (press enter and run the makefile)

• Keywords: overlapping
  
• References: http://www.ubu.com/sound/lucier.html, http://www.ubu.com/film/serra_boomerang.html
• Necessary Equipment: 1 set of headphones/loudspeaker, 1 microphone, 1 laptop, >1 oral scanner poets, USB audio interface
  
• Dependencies:
  

  PocketSphinx package `sudo aptitude install pocketsphinx pocketsphinx-en-us`

  PocketSphinx: `sudo pip3 install PocketSphinx`

  Python libraries: `sudo apt-get install gcc automake autoconf libtool bison swig python-dev libpulse-dev`

  Speech Recognition: `sudo pip3 install SpeechRecognition`

  TermColor: `sudo pip3 install termcolor`

  PyAudio: `pip3 install pyaudio`

• Software:
  

  ttssr_transcribe.py
  

  ttssr_write_audio.py
  

  ttssr-loop-human-only.sh:

#!/bin/bash
i=0;
echo "Read every new sentence out loud!"
head -n 1 $1 > output/input0.txt
while [[ $i -le 10 ]]
	do echo $i
	cat output/input$i.txt 
	python3 src/write_audio.py src/sound$i.wav 2> /dev/null
	play src/sound$i.wav repeat 5 2> /dev/null &
	python3 src/audio_transcribe.py sound$i.wav > output/input$((i+1)).txt 2> /dev/null
	sleep 
	(( i++ ))
done
today=$(date +%Y%m%d.%H-%M);
mkdir -p "output/ttssr.$today"
mv -v output/input* output/ttssr.$today;
mv -v src/sound* output/ttssr.$today;

Common makefile:

ttssr-human-only: ocr/output.txt

bash src/ttssr-loop-human-only.sh ocr/output.txt

• Trying out

Input: (You can choose any of the scanned texts you like)

Any one is one having been that one Any one is such a one. From "Many Many Many Women", Gerdrude Stein

First output: (In the beginning I ask for this:"Read every new sentence out loud!")

0
Any one is one having been that one Any one is such a one.
1
anyone is one haven't been that the one anyone except to wind
2
anyone is one happening that they want anyone except the week
3
anyone is one happening that they want anyone except the week
4
anyone is one happening that they want anyone except that we
5
anyone is one happy that they want anyone except that we
6
anyone is one happy that they want anyone except at the week
7
anyone is one happy that they want anyone except that they were
8
anyone is one happy that they want anyone except
9
and when is one happy that they want anyone except
10
and when is one happy that they want anyone makes

Second output: (In the beginning I ask for this:

"Read every new sentence out loud!")

0
Any one is one having been that one Any one is such a one.
1
anyone is one haven't been that the one anyone is set to wind
2
anyone nice one haven't been that they want anyone is said to weep
3
anyone nice one half and being that they want anyone he said to pretend
4
anyone awhile nice white house and being that they want anyone he said to prevent this
5
anyone awhile nice white house and the bed they want anyone he said to prevent these
6
anyone awhile nice white house and the bed they want anyone he said to prevent aids
7
anyone awhile nice white house and a bed they want anyone he said to prevent aids
8
anyone awhile nice white house and the bed they want anyone he said to prevent aids
9
anyone awhile nice white house and the bed they want and when he said to prevent a
10
anyone know what nice white house and the bed they want and when he said to prevent an

Third output:

Algologs presentation (at Varia)