159 lines
3.2 KiB
Python
159 lines
3.2 KiB
Python
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()) |