moving forward
This commit is contained in:
gauthiier
parent
11201664b8
commit
ffa298a1fd
23
config.json
23
config.json
@ -1,29 +1,34 @@
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{
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"voices": [
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{
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"name": "Ralph",
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"name": "ETHER",
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"model_dir": "data/tokens+models/Emerson-Nature.txt_bs=64_ns=8000_vs=5000",
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"tokeniser_file": "data/tokens+models/Emerson-Nature.txt_bs=64_ns=8000_vs=5000/Emerson-Nature.txt_ns=5000.tokenizer.json",
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"temperature": "0.9"
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},
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{
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"name": "Jean",
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"model_dir": "data/tokens+models/Lafontaine-Fables[english].txt_bs=64_ns=8000_vs=5000",
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"tokeniser_file": "data/tokens+models/Lafontaine-Fables[english].txt_bs=64_ns=8000_vs=5000/Lafontaine-Fables[english].txt_ns=5000.tokenizer.json",
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"name": "CHAOS",
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"model_dir": "data/tokens+models/Lafontaine-Fables[english].txt_bs=64_ns=3000_vs=5000",
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"tokeniser_file": "data/tokens+models/Lafontaine-Fables[english].txt_bs=64_ns=3000_vs=5000/Lafontaine-Fables[english].txt_ns=5000.tokenizer.json",
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"temperature": "1.2"
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},
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{
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"name": "Blake",
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"model_dir": "data/tokens+models/Blake-Songs-of-Innocence-and-of-Experience.txt_bs=64_ns=8000_vs=5000",
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"tokeniser_file": "data/tokens+models/Blake-Songs-of-Innocence-and-of-Experience.txt_bs=64_ns=8000_vs=5000/Blake-Songs-of-Innocence-and-of-Experience.txt_ns=5000.tokenizer.json",
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"name": "BLAKE",
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"model_dir": "data/tokens+models/Blake-Songs-of-Innocence-and-of-Experience.txt_bs=64_ns=3000_vs=5000",
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"tokeniser_file": "data/tokens+models/Blake-Songs-of-Innocence-and-of-Experience.txt_bs=64_ns=3000_vs=5000/Blake-Songs-of-Innocence-and-of-Experience.txt_ns=5000.tokenizer.json",
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"temperature": "1.5"
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},
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{
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"name": "Friedrich",
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"name": "THEO",
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"model_dir": "data/tokens+models/Schelling-ON-THE-RELATION-OF-THE-PLASTIC-ARTS-TO-NATURE.txt_bs=64_ns=8000_vs=5000",
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"tokeniser_file": "data/tokens+models/Schelling-ON-THE-RELATION-OF-THE-PLASTIC-ARTS-TO-NATURE.txt_bs=64_ns=8000_vs=5000/Schelling-ON-THE-RELATION-OF-THE-PLASTIC-ARTS-TO-NATURE.txt_ns=5000.tokenizer.json",
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"temperature": "1.5"
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},
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{
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"name": "POMPOM",
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"model_dir": "data/tokens+models/NEWNATUREPOEMS.txt_bs=64_ns=5000_vs=5000",
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"tokeniser_file": "data/tokens+models/NEWNATUREPOEMS.txt_bs=64_ns=5000_vs=5000/NEWNATUREPOEMS.txt_ns=5000.tokenizer.json",
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"temperature": "0.5"
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}
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]
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}
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113
speak_broadcast.py
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113
speak_broadcast.py
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import argparse, json, sys, time, random
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import utterance.voice
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import utterance.utils
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import utterance.osc
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import examine.metric
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UTTERANCE_LEN = 16
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broadcast = None
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def format_str(text: str) -> str:
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t = utterance.utils.clean(text)
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return utterance.utils.format(t)
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def broadcast_utterance(v, utterance):
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global broadcast
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text = v.name.upper() + ":\n"
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broadcast.utterance(text, v.channel)
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time.sleep(2)
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frags = v.fragments(utterance)
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for f in frags:
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text += f
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broadcast.utterance(text, v.channel)
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time.sleep(2)
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broadcast.command('clear')
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time.sleep(2)
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def main() -> int:
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global broadcast
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p = argparse.ArgumentParser()
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p.add_argument("-c", "--config", type=str, default="voice.config.json", help="configuratin file")
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p.add_argument("-i", "--iterations", type=int, default=10, help="number of iterations")
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args = p.parse_args()
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with open(args.config) as f:
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conf = json.load(f)
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voices = []
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for v in conf['voices']:
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model = v['model']
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voice = utterance.voice.Voice(name=v["name"].upper(), model=model['model_dir'], tokenizer=model['tokeniser_file'], temp=float(model["temperature"]), lenght=UTTERANCE_LEN)
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voice.set_channel(v['osc_channel']['root'], v['osc_channel']['utterance'])
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voices.append(voice)
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broadcast = utterance.osc.OscBroadcaster(name="osc_broadcast", host=conf['host'], port=conf['port'], command_channel=conf['command_osc_channel'])
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broadcast.start_osc()
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nbr_voices = len(voices)
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state = 'c'
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metric = examine.metric.Metric(model_input='data/models/doc2vec.model')
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s = set(range(0, nbr_voices - 1))
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rindex = random.sample(s, 1)[0]
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v = voices[rindex]
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uv = v.utter_one()
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uv = format_str(uv)
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v_vec = metric.vector(uv)
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while state == 'c':
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candidates = random.sample(s, 3)
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results = []
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for c in candidates:
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if c == rindex:
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continue
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vc = voices[c]
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vc_texts = vc.utter_n(n=50)
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for t in vc_texts:
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t = format_str(t)
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t_vec = metric.vector(t)
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d = examine.metric.cos_dist(v_vec, t_vec)
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results.append([d, t, c])
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results.sort(key=lambda t: t[0], reverse=True)
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broadcast_utterance(v, uv)
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# new round
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top = results[0]
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rindex = top[2]
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v = voices[rindex]
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uv = top[1]
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v_vec = metric.vector(top[1])
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# state = input("Continue? ")
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broadcast.terminate_osc()
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if __name__ == '__main__':
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sys.exit(main())
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@ -1,8 +1,11 @@
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import argparse, json, sys, time, random
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import utterance.voice
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import utterance.utils
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import utterance.osc
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import examine.metric
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UTTERANCE_LEN = 16
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def format_str(text: str) -> str:
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t = utterance.utils.clean(text)
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return utterance.utils.format(t)
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def main() -> int:
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p = argparse.ArgumentParser()
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p.add_argument("-c", "--config", type=str, default="config.json", help="configuratin file")
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p.add_argument("-c", "--config", type=str, default="voice.config.json", help="configuratin file")
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p.add_argument("-i", "--iterations", type=int, default=10, help="number of iterations")
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args = p.parse_args()
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print(args)
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with open(args.config) as f:
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conf = json.load(f)
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voices = []
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for v in conf['voices']:
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voice = utterance.voice.Voice(name=v["name"].upper(), model=v['model_dir'], tokenizer=v['tokeniser_file'], temp=float(v["temperature"]), lenght=16)
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model = v['model']
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voice = utterance.voice.Voice(name=v["name"].upper(), model=model['model_dir'], tokenizer=model['tokeniser_file'], temp=float(model["temperature"]), lenght=UTTERANCE_LEN)
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voice.set_channel(v['osc_channel']['root'], v['osc_channel']['utterance'])
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voices.append(voice)
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broadcast = utterance.osc.OscBroadcaster(name="osc_broadcast", host=conf['host'], port=conf['port'], command_channel=conf['command_osc_channel'])
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broadcast.start_osc()
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nbr_voices = len(voices)
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state = 'c'
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@ -94,23 +100,7 @@ def main() -> int:
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# nbr_voices = len(voices)
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# current_voice = ""
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# for i in range(args.iterations):
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# rindex = random.randint(0, nbr_voices - 1)
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# v = voices[rindex]
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# if v.name != current_voice:
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# print("==========")
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# print(v.name + ":")
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# current_voice = v.name
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# t = v.utter_one()
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# if t != None:
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# t = utterance.utils.clean(t)
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# t = utterance.utils.format(t)
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# print(t)
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# time.sleep(4)
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broadcast.terminate_osc()
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if __name__ == '__main__':
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159
speak_metric_broadcast.py
Normal file
159
speak_metric_broadcast.py
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import argparse, json, sys, time, random
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import utterance.voice
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import utterance.utils
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import examine.metric
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from osc4py3.as_eventloop import *
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from osc4py3 import oscbuildparse
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voices_broadcast = {}
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conf = {}
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def init_broadcast():
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global conf, voices_broadcast
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with open('voice.config.json') as f:
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conf = json.load(f)
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# configure voices and their channels
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for v in conf['voices']:
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voices_broadcast[v['name']] = v['osc_channel']['root'] + v['osc_channel']['utterance']
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print(voices_broadcast)
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# Start the system.
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osc_startup()
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# Make client channels to send packets.
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osc_udp_client(conf['host'], conf['port'], "aaaa")
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def broadcast_utterance(name, utterance):
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global conf, voices_broadcast
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sentences = utterance.split('\n')
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text = name + ":"
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for t in sentences:
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if ',' in t:
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phrases = t.split(',')
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for i in range(0, len(phrases)):
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p = phrases[i]
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if p != "":
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text += " " + p
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if i != len(phrases) - 1 :
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text += ','
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msg = oscbuildparse.OSCMessage(voices_broadcast[name], None, [text])
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osc_send(msg, "aaaa")
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osc_process()
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time.sleep(2)
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else:
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if text == "":
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text += t
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else:
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text += "\n" + t
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msg = oscbuildparse.OSCMessage(voices_broadcast[name], None, [text])
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osc_send(msg, "aaaa")
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osc_process()
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time.sleep(2)
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msg = oscbuildparse.OSCMessage(conf['command_osc_channel'], None, ["clear"])
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osc_send(msg, "aaaa")
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osc_process()
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def format_str(text: str) -> str:
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t = utterance.utils.clean(text)
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return utterance.utils.format(t)
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def main() -> int:
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p = argparse.ArgumentParser()
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p.add_argument("-c", "--config", type=str, default="config.json", help="configuratin file")
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p.add_argument("-i", "--iterations", type=int, default=10, help="number of iterations")
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args = p.parse_args()
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print(args)
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with open(args.config) as f:
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conf = json.load(f)
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voices = []
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for v in conf['voices']:
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voice = utterance.voice.Voice(name=v["name"].upper(), model=v['model_dir'], tokenizer=v['tokeniser_file'], temp=float(v["temperature"]), lenght=7)
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voices.append(voice)
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init_broadcast()
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nbr_voices = len(voices)
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state = 'c'
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metric = examine.metric.Metric(model_input='data/models/doc2vec.model')
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s = set(range(0, nbr_voices - 1))
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# rindex = random.sample(s, 1)[0]
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rindex = 4
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v = voices[rindex]
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uv = v.utter_one()
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uv = format_str(uv)
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v_vec = metric.vector(uv)
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while 1:
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candidates = random.sample(s, 2)
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results = []
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for c in candidates:
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if c == rindex:
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continue
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vc = voices[c]
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vc_texts = vc.utter_n(n=25)
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for t in vc_texts:
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t = format_str(t)
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t_vec = metric.vector(t)
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d = examine.metric.cos_dist(v_vec, t_vec)
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results.append([d, t, c])
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results.sort(key=lambda t: t[0], reverse=True)
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# print('----------------------------')
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# print(v.name + ":")
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# print(uv)
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# print('----------------------------')
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broadcast_utterance(v.name, uv)
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# for r in results[:2]:
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# print('-->' + str(r[0]))
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# print(r[1])
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# print('+++++++++++++++++++++++++')
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# new round
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top = results[0]
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rindex = top[2]
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v = voices[rindex]
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uv = top[1]
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v_vec = metric.vector(top[1])
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# state = input("Continue? ")
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osc_terminate()
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if __name__ == '__main__':
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sys.exit(main())
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34
utterance/osc.py
Normal file
34
utterance/osc.py
Normal file
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from osc4py3.as_eventloop import *
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from osc4py3 import oscbuildparse
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class OscBroadcaster:
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def __init__(self, name: str, host: str, port: str, command_channel: str):
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self.name = name
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self.host = host
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self.port = port
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self.cmd = command_channel
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osc_udp_client(self.host, self.port, self.name)
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def utterance(self, utterance: str, channel: str):
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msg = oscbuildparse.OSCMessage(channel, None, [utterance])
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osc_send(msg, self.name)
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osc_process()
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def command(self, command: str):
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msg = oscbuildparse.OSCMessage(self.cmd, None, [command])
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osc_send(msg, self.name)
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osc_process()
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@staticmethod
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def start_osc():
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osc_startup()
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@staticmethod
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def terminate_osc():
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osc_terminate()
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@ -1,4 +1,4 @@
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import string
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import string, regex
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def clean(text: str) -> str:
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@ -17,3 +17,32 @@ def clean(text: str) -> str:
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def format(text: str) -> str:
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return text.replace('\r\n', '\n').replace('\n\n', '\n')
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def fragments(utterance: str):
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frags = []
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sentences = utterance.splitlines()
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PUNCT_RE = regex.compile(r'(\p{Punctuation})')
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for s in sentences:
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sf = PUNCT_RE.split(s)
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cum = ""
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for k in sf:
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if len(k) < 1:
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continue
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elif len(k) > 1:
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cum += k
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elif k not in string.punctuation:
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cum += k
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else:
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cum += k
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frags.append(cum)
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cum = ""
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cum += '\n'
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frags.append(cum)
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return frags
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@ -1,5 +1,6 @@
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from aitextgen import aitextgen
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import utterance.utils
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import regex, string
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class Voice:
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@ -16,3 +17,17 @@ class Voice:
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def utter_one(self, temp: int = None, lenght: float = None) -> str:
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return self.utter_n(n=1, temp=temp, lenght=lenght)[0]
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def set_channel(self, root: str, endpoint: str):
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self.channel = root + endpoint
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def channel(self):
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return self.channel
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def fragments(self, utt: str):
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self.utterance = utt
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self.utterance_fragments = utterance.utils.fragments(utt)
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return self.utterance_fragments
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107
voice.config.json
Normal file
107
voice.config.json
Normal file
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{
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"command_osc_channel" : "/command",
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"host" : "127.0.0.1",
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||||
"port" : "1111",
|
||||
"voices" : [
|
||||
{
|
||||
"background" : "0xff571111",
|
||||
"color" : "0xffc8d75d",
|
||||
"font" : "Times New Roman",
|
||||
"name" : "CHAOS",
|
||||
"osc_channel" : {
|
||||
"background" : "/background",
|
||||
"color" : "/font/color",
|
||||
"root" : "/chaos",
|
||||
"size" : "/font/size",
|
||||
"type" : "/font/type",
|
||||
"utterance" : "/utterance"
|
||||
},
|
||||
"model" :{
|
||||
"model_dir": "data/tokens+models/Lafontaine-Fables[english].txt_bs=64_ns=3000_vs=5000",
|
||||
"tokeniser_file": "data/tokens+models/Lafontaine-Fables[english].txt_bs=64_ns=3000_vs=5000/Lafontaine-Fables[english].txt_ns=5000.tokenizer.json",
|
||||
"temperature": "1.2"
|
||||
},
|
||||
"size" : 100
|
||||
},
|
||||
{
|
||||
"background" : "0xff020000",
|
||||
"color" : "0xffebf3f1",
|
||||
"font" : "Arial-BoldMT",
|
||||
"name" : "ETHER",
|
||||
"osc_channel" : {
|
||||
"background" : "/background",
|
||||
"color" : "/font/color",
|
||||
"root" : "/ether",
|
||||
"size" : "/font/size",
|
||||
"type" : "/font/type",
|
||||
"utterance" : "/utterance"
|
||||
},
|
||||
"model" :{
|
||||
"model_dir": "data/tokens+models/Emerson-Nature.txt_bs=64_ns=8000_vs=5000",
|
||||
"tokeniser_file": "data/tokens+models/Emerson-Nature.txt_bs=64_ns=8000_vs=5000/Emerson-Nature.txt_ns=5000.tokenizer.json",
|
||||
"temperature": "0.9"
|
||||
},
|
||||
"size" : 100
|
||||
},
|
||||
{
|
||||
"background" : "0xffdcb213",
|
||||
"color" : "0xff353a39",
|
||||
"font" : "NotoSansVai-Regular",
|
||||
"name" : "BLAKE",
|
||||
"osc_channel" : {
|
||||
"background" : "/background",
|
||||
"color" : "/font/color",
|
||||
"root" : "/blake",
|
||||
"size" : "/font/size",
|
||||
"type" : "/font/type",
|
||||
"utterance" : "/utterance"
|
||||
},
|
||||
"model" :{
|
||||
"model_dir": "data/tokens+models/Blake-Songs-of-Innocence-and-of-Experience.txt_bs=64_ns=3000_vs=5000",
|
||||
"tokeniser_file": "data/tokens+models/Blake-Songs-of-Innocence-and-of-Experience.txt_bs=64_ns=3000_vs=5000/Blake-Songs-of-Innocence-and-of-Experience.txt_ns=5000.tokenizer.json",
|
||||
"temperature": "1.5"
|
||||
},
|
||||
"size" : 100
|
||||
},
|
||||
{
|
||||
"background" : "0xff020000",
|
||||
"color" : "0xffebf3f1",
|
||||
"font" : "Arial-BoldMT",
|
||||
"name" : "POMPOM",
|
||||
"osc_channel" : {
|
||||
"background" : "/background",
|
||||
"color" : "/font/color",
|
||||
"root" : "/pompom",
|
||||
"size" : "/font/size",
|
||||
"type" : "/font/type",
|
||||
"utterance" : "/utterance"
|
||||
},
|
||||
"model" :{
|
||||
"model_dir": "data/tokens+models/NEWNATUREPOEMS.txt_bs=64_ns=5000_vs=5000",
|
||||
"tokeniser_file": "data/tokens+models/NEWNATUREPOEMS.txt_bs=64_ns=5000_vs=5000/NEWNATUREPOEMS.txt_ns=5000.tokenizer.json",
|
||||
"temperature": "0.5"
|
||||
},
|
||||
"size" : 100
|
||||
},
|
||||
{
|
||||
"background" : "0xff571111",
|
||||
"color" : "0xffc8d75d",
|
||||
"font" : "Times New Roman",
|
||||
"name" : "THEO",
|
||||
"osc_channel" : {
|
||||
"background" : "/background",
|
||||
"color" : "/font/color",
|
||||
"root" : "/theo",
|
||||
"size" : "/font/size",
|
||||
"type" : "/font/type",
|
||||
"utterance" : "/utterance"
|
||||
},
|
||||
"model" :{
|
||||
"model_dir": "data/tokens+models/Schelling-ON-THE-RELATION-OF-THE-PLASTIC-ARTS-TO-NATURE.txt_bs=64_ns=8000_vs=5000",
|
||||
"tokeniser_file": "data/tokens+models/Schelling-ON-THE-RELATION-OF-THE-PLASTIC-ARTS-TO-NATURE.txt_bs=64_ns=8000_vs=5000/Schelling-ON-THE-RELATION-OF-THE-PLASTIC-ARTS-TO-NATURE.txt_ns=5000.tokenizer.json",
|
||||
"temperature": "1.5"
|
||||
},
|
||||
"size" : 100
|
||||
}
|
||||
]
|
||||
}
|
||||
Loading…
x
Reference in New Issue
Block a user