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https://github.com/ziligy/watson-text-talker
Simple python Text-to-Speech Interface using IBM's Watson TTS
https://github.com/ziligy/watson-text-talker
bot home-automation pip python raspberry-pi text-to-speech voice watson
Last synced: 4 days ago
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Simple python Text-to-Speech Interface using IBM's Watson TTS
- Host: GitHub
- URL: https://github.com/ziligy/watson-text-talker
- Owner: ziligy
- License: mit
- Created: 2018-07-31T23:38:29.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2019-10-22T22:34:01.000Z (over 5 years ago)
- Last Synced: 2025-01-16T13:40:04.375Z (6 days ago)
- Topics: bot, home-automation, pip, python, raspberry-pi, text-to-speech, voice, watson
- Language: Python
- Homepage:
- Size: 13.7 KB
- Stars: 6
- Watchers: 1
- Forks: 1
- Open Issues: 4
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# watson-text-talker
### About
I created this interface for a voice-based-bot that I'm running on a Raspberry Pi 3B. I'm using the AIY Voice HAT, but I was very displeased with the robotic-voice that's supplied by Google. After studying a few other voice options I decided on IBM's Watson because of it's high quality cadence and intonation. I added some features for my purposes and decided others may find some benefit in my effort. The package should work in other internet-connected & sound-output-capable devices.
### Installation
pip3 install watson-text-talker --user
### Get [IBM credentials](https://console.bluemix.net/catalog/services/text-to-speech) for Watson Text-To-Speech, Lite Plan is *FREE*
### Simple Use
```python
from watson_text_talker import *
text_talker = TextTalker(api_key='your-watson-tts-api-key')
text_talker.say("Hello world!")
```
### Features
* #### Voice file cacheing
- lowers cloud round-trips
- keeps cost down
* #### Phrase grouping
- segments phrases/sentences
- each segment can have it's own importance factor
* #### Importance factors
- optional percentage chance that a phrase will be voiced
* #### Quiet level
- optional quiet level factor can be applied to all optional phrases
- increases or decreases the likelihood that an optional phrase will be voiced
* #### Uses high-quality Waston voices
- very realistic sounding, with appropriate cadence and intonation
- voice selection: [see here for selection available](https://www.ibm.com/watson/developercloud/text-to-speech/api/v1/curl.html?curl#get-voice)
- free tier plan: no credit card required, 10,000 characters per month at no cost
### Voice file cacheing
The package *always* caches new phrases to a file. The cache directory defaults to `./voice_mp3s`, but can also be defined in TT_Config. To regulate the filename I slugify the phrase. This has the advantage of making it human readable. The only caveat is the phrase MUST be limited to 255 characters.
### Phrase grouping
Phrase grouping is based on array of tuples.
```python
from watson_text_talker import *
text_talker = TextTalker(api_key='your-api-key')
importance = TT_Importance()
grouping_example = [(importance.SAY_30_PERCENT, "I'm your assistant."), (importance.SAY_50_PERCENT, "How are you?"), (importance.SAY_ALWAYS, "Nice to meet you") ]
text_talker.say_group(grouping_example)
```
Tuples are made up of the importance & the text phrase.
### Importance factors
```python
# TT_Importance is a class of numeric constants
SAY_ALWAYS = 1
SAY_90_PERCENT = 2
SAY_80_PERCENT = 3
SAY_70_PERCENT = 4
SAY_60_PERCENT = 5
SAY_50_PERCENT = 6
SAY_40_PERCENT = 7
SAY_30_PERCENT = 8
SAY_20_PERCENT = 9
SAY_10_PERCENT = 10
SAY_NEVER = 11
```
For the same as above we could have just as easily said:
```python
from watson_text_talker import *
text_talker = TextTalker(api_key='your_api_key')
grouping_example = [(8, "I'm your assistant."), (6, "How are you?"), (1, "Nice to meet you") ]
text_talker.say_group(grouping_example)
```
### Quiet level
The package includes a globally applied `quite level` that increases or decreases the likelihood that an optional phrase will be voiced.
```python
from watson_text_talker import *
text_talker = TextTalker(api_key='your_api_key')
importance = TT_Importance()
grouping_example = [(importance.SAY_30_PERCENT, "I'm your assistant."), (importance.SAY_ALWAYS, "Nice to meet you") ]
text_talker.quiet_level = +2
text_talker.say_group(grouping_example)
```
In the above example the `I'm your assistant` phrase will only be said 10% of the time because of the +2 assigned to quiet level. The `Nice to meet you` is not effected.
### Config
use the TT_Config class to override configuration defaults
```python
# TT_Config's standard defaults
API_KEY='--watson tts credentials api-key goes here--'
# TTS API URL
API_URL='https://gateway-lon.watsonplatform.net/text-to-speech/api'
TTS_VOICE = 'en-US_AllisonVoice'
TTS_ACCEPT = 'audio/mp3'
CACHE_DIRECTORY = 'voice_mp3s'
# when True cache direcory will be relative to the current working directory
# if False then cache directory should be fully pathed
CACHE_DIRECTORY_IS_RELATIVE = True
VOICE_FILE_EXTENSION = 'mp3'
# some environments may require a delay if first speech is cut off
# generally 1, 2 or 3 seconds will work
INITIALIZATION_DELAY = 0
```
Use it like so:
```python
from watson_text_talker import *
config = TT_Config()
config.API_KEY='your watson tts api-key'
config.API_URL='if you need to update API URL, update this'
config.TTS_Voice = 'en-US_MichaelVoice'
congig.CACHE_DIRECTORY = 'custom_cache'
congig.INITIALIZATION_DELAY = 1
text_talker = TextTalker(config=config)
text_talker.say("Hello world!")
```
### Attributions
* [pygame](https://github.com/pygame/pygame) is used to process the mp3 voice files
* [python-slugify](https://github.com/un33k/python-slugify) is used to create cache file names