File size: 37,589 Bytes
b40d021
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
a302f14
b40d021
 
a302f14
b40d021
 
 
 
a302f14
b40d021
a302f14
b40d021
 
 
 
a302f14
b40d021
 
a302f14
b40d021
2349f4b
5b5d1ff
2349f4b
 
5b5d1ff
2349f4b
 
e85ca7f
2349f4b
 
 
5b5d1ff
e85ca7f
2349f4b
5b5d1ff
e85ca7f
b40d021
 
a302f14
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
b40d021
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
a302f14
b40d021
a302f14
b40d021
a302f14
b40d021
 
 
a302f14
b40d021
a302f14
b40d021
 
 
 
 
 
 
2349f4b
8471ef2
2349f4b
5b5d1ff
 
 
8471ef2
5b5d1ff
8471ef2
5b5d1ff
8471ef2
 
 
 
 
2349f4b
 
8471ef2
 
 
 
 
 
 
5b5d1ff
8471ef2
 
2349f4b
8471ef2
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
2349f4b
 
8471ef2
 
2349f4b
 
 
 
 
 
8471ef2
 
 
 
 
 
 
2349f4b
 
 
 
 
 
b40d021
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
ecd9a57
 
 
a148682
 
1dc8345
a148682
1dc8345
a148682
1dc8345
a148682
 
1dc8345
 
 
ecd9a57
9aa3a30
 
 
ecd9a57
 
 
9aa3a30
ecd9a57
 
 
 
 
 
 
 
9aa3a30
ecd9a57
 
9aa3a30
ecd9a57
 
9aa3a30
 
 
 
ecd9a57
 
9aa3a30
 
 
ecd9a57
 
 
 
 
 
 
 
 
9aa3a30
ecd9a57
 
 
9aa3a30
e8e523e
 
ecd9a57
 
9aa3a30
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
e8e523e
 
9aa3a30
ecd9a57
 
b40d021
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
8372e28
e85ca7f
8372e28
e85ca7f
8372e28
e85ca7f
8372e28
e85ca7f
 
 
8372e28
 
 
 
 
 
b40d021
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
a14a754
b40d021
a14a754
 
f715ece
b40d021
 
f715ece
b40d021
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
a302f14
b40d021
 
 
 
 
 
a302f14
b40d021
 
 
d7e7fc6
 
 
 
 
 
 
b40d021
e85ca7f
 
9aa3a30
2349f4b
 
 
 
e85ca7f
b40d021
d7e7fc6
 
b40d021
 
 
 
 
e85ca7f
b40d021
 
 
 
 
9aa3a30
d7e7fc6
 
 
b40d021
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
a302f14
 
 
b40d021
5b5d1ff
2349f4b
e85ca7f
b40d021
 
 
a302f14
b40d021
 
a302f14
b40d021
a302f14
b40d021
a302f14
b40d021
a302f14
 
b40d021
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
1001
1002
1003
1004
1005
1006
1007
1008
1009
1010
1011
1012
1013
1014
1015
1016
1017
1018
1019
1020
1021
1022
1023
1024
1025
1026
1027
1028
1029
1030
1031
1032
1033
1034
1035
1036
1037
1038
1039
1040
1041
1042
1043
1044
1045
1046
1047
1048
1049
1050
1051
1052
1053
1054
1055
1056
1057
1058
1059
1060
1061
1062
1063
1064
1065
1066
1067
1068
1069
1070
1071
1072
1073
1074
1075
1076
1077
1078
1079
1080
1081
1082
1083
1084
1085
1086
1087
1088
1089
1090
1091
1092
1093
1094
1095
1096
1097
1098
1099
1100
1101
1102
1103
1104
1105
1106
1107
1108
1109
1110
1111
1112
1113
1114
1115
1116
1117
1118
1119
1120
1121
1122
1123
1124
1125
1126
1127
1128
1129
1130
# -*- coding: utf-8 -*-
import numpy as np
import librosa
import gradio as gr
from dataclasses import dataclass
from sklearn.linear_model import Ridge
from sklearn.preprocessing import StandardScaler
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score

"""音声分類.ipynb

Automatically generated by Colab.

Original file is located at
    https://colab.research.google.com/drive/1_wgDxDY2B0aYe_zbc1yZ603NBXlRc6Xe
"""

# ESN
@dataclass
class ESNConfig:
    n_res: int = 500
    spectral_radius: float = 0.9
    leaking_rate: float = 0.3
    input_scale: float = 0.5
    sparsity: float = 0.95
    ridge_alpha: float = 1e-3
    seed: int = 42

class ESNClassifier:
    def __init__(self, cfg: ESNConfig, n_in: int, n_classes: int):
        self.cfg = cfg
        self.n_in = n_in
        self.n_classes = n_classes
        self.rng = np.random.default_rng(cfg.seed)

        self.W_in = (self.rng.uniform(-1, 1, (cfg.n_res, n_in)) * cfg.input_scale).astype(np.float32)

        W = self.rng.uniform(-1, 1, (cfg.n_res, cfg.n_res)).astype(np.float32)
        mask = self.rng.uniform(0, 1, W.shape) < cfg.sparsity
        W[mask] = 0.0

        v = self.rng.normal(size=(cfg.n_res,)).astype(np.float32)
        v /= np.linalg.norm(v) + 1e-12
        for _ in range(50):
            v = W @ v
            v /= np.linalg.norm(v) + 1e-12
        approx = np.linalg.norm(W @ v)
        if approx > 0:
            W *= cfg.spectral_radius / approx
        self.W_res = W

        self.scaler = StandardScaler()
        self.readout = Ridge(alpha=cfg.ridge_alpha)
        self.reset_state()

    def reset_state(self):
        self.x = np.zeros(self.cfg.n_res, dtype=np.float32)

    def step(self, u):
        pre = self.W_in @ u + self.W_res @ self.x
        x_new = np.tanh(pre)
        a = self.cfg.leaking_rate
        self.x = (1 - a) * self.x + a * x_new
        return self.x

    def sequence_feature(self, U):
        self.reset_state()
        states = []
        for u in U:
            states.append(self.step(u))
        states = np.stack(states)
        feat = np.concatenate([states.mean(0), states[-1]])
        return feat

    def fit(self, X_list, y_list):
        feats = np.stack([self.sequence_feature(U) for U in X_list])
        feats = self.scaler.fit_transform(feats)
        Y = np.eye(self.n_classes)[y_list]
        self.readout.fit(feats, Y)

    def predict_proba_sequence(self, U):
        feat = self.sequence_feature(U)[None]
        feat = self.scaler.transform(feat)
        y = self.readout.predict(feat)[0]
        y -= np.max(y)
        return np.exp(y) / (np.sum(np.exp(y)) + 1e-12)

    def predict_step_proba(self, u):
        x = self.step(u)
        feat = np.concatenate([x, x])[None]
        feat = self.scaler.transform(feat)
        y = self.readout.predict(feat)[0]
        y -= np.max(y)
        return np.exp(y) / (np.sum(np.exp(y)) + 1e-12)

# Audio -> MFCC
SR = 16000
N_MFCC = 13
HOP = int(0.01 * SR)
WIN = int(0.025 * SR)

def _mono_float32(y):
    y = y.astype(np.float32)
    if y.ndim > 1:
        y = y.mean(axis=1)
    return y

def normalize_audio_tuple(audio):
    # audio: (sr, y)
    sr, y = audio
    y = _mono_float32(y)
    if sr != SR:
        y = librosa.resample(y, orig_sr=sr, target_sr=SR)
        sr = SR
    y /= (np.max(np.abs(y)) + 1e-9)
    return (sr, y)

def audio_to_sequence(audio):
    sr, y = normalize_audio_tuple(audio)
    mfcc = librosa.feature.mfcc(y=y, sr=sr, n_mfcc=N_MFCC, hop_length=HOP, n_fft=WIN)
    return mfcc.T.astype(np.float32)

def chunk_to_seq(chunk):
    if chunk is None:
        return None
    sr, y = chunk
    if y is None:
        return None
    y = _mono_float32(y)
    if len(y) < WIN:
        return None
    return audio_to_sequence(chunk)

# Data store (replay + relabel)
# each item: {"audio": (sr,y), "U": mfcc_seq, "label": str}
DATA = []
LABELS = []
MODEL = None

def probs_dict_from_p(p):
    if p is None or len(LABELS) == 0:
        return {}
    return {LABELS[i]: float(p[i]) for i in range(min(len(LABELS), len(p)))}

def dataset_table():
    # compact rows: idx, label, sec
    rows = []
    for i, item in enumerate(DATA):
        sr, y = item["audio"]
        dur = (len(y) / sr) if (sr and y is not None) else 0.0
        rows.append([i, item["label"], round(dur, 2)])
    return rows

def dataset_stats_text():
    counts = {l: 0 for l in LABELS}
    for item in DATA:
        lab = item["label"]
        counts[lab] = counts.get(lab, 0) + 1
    parts = [f"{l}:{counts.get(l,0)}" for l in LABELS] if LABELS else ["(no labels)"]
    return f"n={len(DATA)} | " + " ".join(parts)

# Training
def train_random(n_trials):
    global MODEL
    if len(LABELS) < 2:
        return "ラベル不足(2種類以上)"
    if len(DATA) < 6:
        return "データ不足(目安: 合計6以上、各ラベル3以上)"

    X = [d["U"] for d in DATA]
    y = [LABELS.index(d["label"]) for d in DATA]

    try:
        X_tr, X_val, y_tr, y_val = train_test_split(
            X, y, test_size=0.3, random_state=0, stratify=y
        )
    except Exception:
        X_tr, X_val, y_tr, y_val = train_test_split(
            X, y, test_size=0.3, random_state=0
        )

    best_acc = -1.0
    best_model = None
    best_cfg = None

    for _ in range(int(n_trials)):
        cfg = ESNConfig(
            n_res=int(np.random.choice([200, 500, 800])),
            spectral_radius=float(np.random.uniform(0.6, 1.2)),
            leaking_rate=float(np.random.uniform(0.1, 0.8)),
            input_scale=float(np.random.uniform(0.1, 1.0)),
            ridge_alpha=float(10 ** np.random.uniform(-5, -2)),
            sparsity=float(np.random.uniform(0.8, 0.98)),
            seed=int(np.random.randint(0, 10_000_000)),
        )
        model = ESNClassifier(cfg, N_MFCC, len(LABELS))
        model.fit(X_tr, y_tr)

        preds = []
        for U in X_val:
            p = model.predict_proba_sequence(U)
            preds.append(int(np.argmax(p)))

        acc = accuracy_score(y_val, preds)
        if acc > best_acc:
            best_acc = acc
            best_model = model
            best_cfg = cfg

    MODEL = best_model
    return f"val acc: {best_acc:.3f} | cfg: {best_cfg}"

# Streaming inference
def stream_predict(chunk, state):
    global MODEL
    if state is None:
        state = {"active": False}

    if MODEL is None:
        state["active"] = False
        return "未学習", {}, state

    U = chunk_to_seq(chunk)
    if U is None:
        if state.get("active", False):
            MODEL.reset_state()
        state["active"] = False
        return "...", {}, state

    if not state.get("active", False):
        MODEL.reset_state()
        state["active"] = True

    p = None
    for u in U:
        p = MODEL.predict_step_proba(u)

    pred = LABELS[int(np.argmax(p))]
    return pred, probs_dict_from_p(p), state

# UI callbacks
def add_label_cb(label):
    label = (label or "").strip()
    if not label:
        return gr.update(), dataset_table(), gr.update()
    if label not in LABELS:
        LABELS.append(label)
    return gr.update(choices=LABELS, value=label), dataset_table(), gr.update(choices=LABELS)

def add_sample_cb(audio, label):
    label = (label or "").strip()
    if label not in LABELS:
        return dataset_table(), gr.update(value=None)
    if audio is None:
        return dataset_table(), gr.update(value=None)

    audio_n = normalize_audio_tuple(audio)
    U = audio_to_sequence(audio_n)
    if U is None or len(U) < 5:
        return dataset_table(), gr.update(value=None)

    DATA.append({"audio": audio_n, "U": U, "label": label})
    return dataset_table(), gr.update(value=None)

def auto_add_sample_cb(audio, label):
    """録音完了(stop_recording)時に自動でDATAに追加"""
    label = (label or "").strip()
    if label not in LABELS:
        return dataset_table(), gr.update(value=None), "⚠ ラベルを先に選択してください"
    if audio is None:
        return dataset_table(), gr.update(value=None), "待機中..."

    audio_n = normalize_audio_tuple(audio)
    U = audio_to_sequence(audio_n)
    if U is None or len(U) < 5:
        return dataset_table(), gr.update(value=None), "⚠ 音声が短すぎます(もう少し話してください)"

    DATA.append({"audio": audio_n, "U": U, "label": label})
    return dataset_table(), gr.update(value=None), f"✓ 保存完了! (idx={len(DATA)-1}, label={label})"

def undo_last_cb():
    if len(DATA) == 0:
        return dataset_table()
    DATA.pop()
    return dataset_table()

def reset_all_cb():
    global MODEL
    DATA.clear()
    LABELS.clear()
    MODEL = None
    return (
        dataset_table(),
        gr.update(choices=[], value=None),
        gr.update(choices=[], value=None),
        gr.update(value=None),
        None,
    )

def clear_rec_cb():
    return gr.update(value=None)

def on_select_row(evt: gr.SelectData):
    # evt.index: (row, col) or row index depending on component
    # For Dataframe select, evt.index is (row, col)
    if evt is None or evt.index is None:
        return None, gr.update(value=None), "未選択"
    row = evt.index[0] if isinstance(evt.index, (tuple, list)) else int(evt.index)
    if row < 0 or row >= len(DATA):
        return None, gr.update(value=None), "範囲外"
    item = DATA[row]
    audio = item["audio"]
    lab = item["label"]
    return audio, gr.update(value=lab), f"selected idx={row}"

def apply_relabel_cb(table, new_label):
    # table is not trusted as source of truth; we use selected_idx in state ideally,
    # but keep simple: infer currently selected by last "selected idx=..."
    # -> we will pass selected index via State.
    return "内部: use state idx"

def relabel_selected_cb(selected_idx, new_label):
    new_label = (new_label or "").strip()
    if selected_idx is None or selected_idx < 0 or selected_idx >= len(DATA):
        return dataset_table()
    if new_label not in LABELS:
        return dataset_table()
    DATA[selected_idx]["label"] = new_label
    return dataset_table()

def delete_selected_cb(selected_idx):
    if selected_idx is None or selected_idx < 0 or selected_idx >= len(DATA):
        return dataset_table(), None, gr.update(value=None)
    DATA.pop(selected_idx)
    return dataset_table(), None, gr.update(value=None)

# Compact UI — Copy.py風フェミニン・パステルデザイン + 写真風ブルー→グリーングラデーション
HEAD = """
<meta name="viewport" content="width=device-width, initial-scale=1, maximum-scale=1, viewport-fit=cover, user-scalable=no">
<link rel="preconnect" href="https://fonts.googleapis.com">
<link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
<link href="https://fonts.googleapis.com/css2?family=Cormorant+Garamond:wght@300;400;500;600&display=swap" rel="stylesheet">
<script>
/* ── 無音自動停止(Gradio公式 .stop-button/.record-button セレクタ使用) ── */
(function(){
  const SILENCE_THRESH = 0.01;
  const SPEECH_THRESH  = 0.015;
  const SILENCE_MS     = 1500;
  let ctx, analyser, src, silStart, spoke, on;

  function stat(m){ var e=document.getElementById('rec_status_js'); if(e) e.textContent=m; }

  function stop(){
    on=false;
    try{src&&src.disconnect()}catch(e){}
    try{ctx&&ctx.close()}catch(e){}
    src=null;ctx=null;analyser=null;
  }

  function monitor(stream){
    stop();
    on=true; spoke=false; silStart=null;
    ctx=new(window.AudioContext||window.webkitAudioContext)();
    analyser=ctx.createAnalyser(); analyser.fftSize=512;
    src=ctx.createMediaStreamSource(stream); src.connect(analyser);
    var buf=new Float32Array(analyser.fftSize);

    function tick(){
      if(!on)return;
      analyser.getFloatTimeDomainData(buf);
      var s=0; for(var i=0;i<buf.length;i++) s+=buf[i]*buf[i];
      var rms=Math.sqrt(s/buf.length);

      if(rms>SPEECH_THRESH){
        spoke=true; silStart=null;
        stat('録音中... 🎙️');
      } else if(spoke && rms<SILENCE_THRESH){
        if(!silStart) silStart=Date.now();
        var left=Math.max(0,SILENCE_MS-(Date.now()-silStart));
        stat('無音検出中... あと'+Math.ceil(left/1000)+'秒');
        if(left<=0){
          stat('自動停止 & 保存中...');
          /* Gradio公式: .stop-button で停止ボタンを取得 */
          var btn=document.querySelector('.stop-button');
          console.log('[auto-stop] .stop-button found:', btn);
          if(btn){ btn.click(); }
          stop();
          return;
        }
      } else if(!spoke){
        stat('待機中... 話してください 🎤');
      }
      requestAnimationFrame(tick);
    }
    tick();
  }

  var orig=navigator.mediaDevices.getUserMedia.bind(navigator.mediaDevices);
  navigator.mediaDevices.getUserMedia=function(c){
    return orig(c).then(function(stream){
      if(c&&c.audio){
        console.log('[auto-stop] getUserMedia intercepted, starting monitor');
        monitor(stream);
        stream.getAudioTracks().forEach(function(t){t.addEventListener('ended',stop);});
      }
      return stream;
    });
  };
})();
</script>
"""

CSS = """
/* ========================================
   グローバル: フェミニン・パステルテーマ
   写真風 淡いブルー→ミントグリーン グラデーション
   ======================================== */
html {
    scroll-behavior: smooth !important;
    -webkit-overflow-scrolling: touch !important;
}

.gradio-container {
    background: linear-gradient(175deg,
        #c5dff0 0%,
        #b8e0e8 15%,
        #b2e5d8 30%,
        #c8ecd0 50%,
        #d5f0cc 70%,
        #e0f4d8 85%,
        #e8f6e0 100%) !important;
    color: #1a1a1a !important;
    font-family: 'Inter', 'Hiragino Kaku Gothic ProN', 'Noto Sans JP', -apple-system, BlinkMacSystemFont, sans-serif !important;
    font-weight: 400 !important;
    max-width: 100% !important;
    padding: 0 !important;
    min-height: 100vh !important;
}

footer { display: none !important; }

/* ========================================
   ヘッダーヒーローセクション
   ======================================== */
.hero-section {
    text-align: center !important;
    padding: 48px 24px 32px 24px !important;
}
.hero-section h1 {
    font-family: 'Cormorant Garamond', 'Georgia', 'Times New Roman', serif !important;
    font-size: clamp(24px, 7vw, 38px) !important;
    font-weight: 400 !important;
    letter-spacing: 0.1em !important;
    color: #2a3a2a !important;
    text-transform: uppercase !important;
    margin: 0 0 8px 0 !important;
    line-height: 1.2 !important;
}
.hero-section p {
    font-size: clamp(12px, 3vw, 14px) !important;
    color: #4a5a4a !important;
    letter-spacing: 0.04em !important;
    margin: 0 !important;
}

/* ========================================
   タブナビゲーション: ピル型パステル
   ======================================== */
div.tab-nav {
    background: rgba(255,255,255,0.75) !important;
    border: 1px solid rgba(0,0,0,0.06) !important;
    border-radius: 22px !important;
    padding: 5px !important;
    margin: 16px 16px 20px 16px !important;
    display: flex !important;
    justify-content: center !important;
    gap: 3px !important;
    box-shadow: 0 2px 12px rgba(100,140,120,0.08) !important;
    backdrop-filter: blur(8px) !important;
    -webkit-backdrop-filter: blur(8px) !important;
}
div.tab-nav button {
    background: transparent !important;
    color: #3a4a3a !important;
    border: none !important;
    border-radius: 18px !important;
    padding: 10px 16px !important;
    font-family: 'Cormorant Garamond', 'Georgia', 'Times New Roman', serif !important;
    font-size: 13px !important;
    font-weight: 500 !important;
    transition: all 0.25s ease !important;
    letter-spacing: 0.1em !important;
}
div.tab-nav button.selected {
    background: rgba(178,216,210,0.4) !important;
    color: #1a2a1a !important;
    box-shadow: 0 1px 8px rgba(178,216,210,0.25) !important;
}

/* ========================================
   タブコンテンツ: 二重フレーム(Copy.py風)
   ======================================== */
.tabitem {
    background: transparent !important;
    border: none !important;
}
.tabitem > div {
    position: relative !important;
    background: rgba(255,255,255,0.92) !important;
    border-radius: 0 !important;
    padding: 32px 20px !important;
    margin: 16px 18px 28px 18px !important;
    border: 1.25px solid #8aaa8a !important;
    box-shadow: 8px 8px 0px 0px #c0d8c0 !important;
    backdrop-filter: blur(4px) !important;
    -webkit-backdrop-filter: blur(4px) !important;
    animation: softFadeIn 0.5s ease forwards;
}

/* ========================================
   ラベル: セリフ体
   ======================================== */
label span, .label-wrap span {
    color: #2a3a2a !important;
    font-family: 'Cormorant Garamond', 'Georgia', 'Times New Roman', serif !important;
    font-weight: 500 !important;
    font-size: 13px !important;
    letter-spacing: 0.06em !important;
}

/* ========================================
   テキスト入力
   ======================================== */
input[type="text"], textarea, select {
    background: rgba(255,255,255,0.8) !important;
    border: 1px solid rgba(138,170,138,0.35) !important;
    border-radius: 0 !important;
    color: #1a1a1a !important;
    font-weight: 400 !important;
}
input[type="text"]:focus, textarea:focus {
    border-color: rgba(138,170,138,0.6) !important;
    box-shadow: 0 0 0 3px rgba(178,216,210,0.2) !important;
    outline: none !important;
}

/* Number input: シャープスタイル */
input[type="number"] {
    background: #ffffff !important;
    border: 1.25px solid #8aaa8a !important;
    border-radius: 0 !important;
    color: #1a1a1a !important;
    font-family: 'Cormorant Garamond', 'Georgia', serif !important;
    font-weight: 500 !important;
    font-size: 13px !important;
    text-align: center !important;
    padding: 4px 6px !important;
    box-shadow: 3px 3px 0px 0px #c0d8c0 !important;
    outline: none !important;
    -moz-appearance: textfield !important;
}
input[type="number"]:focus {
    border-color: #6a8a6a !important;
    box-shadow: 4px 4px 0px 0px #a8c8a8 !important;
}
input[type="number"]::-webkit-inner-spin-button,
input[type="number"]::-webkit-outer-spin-button {
    -webkit-appearance: none !important;
    margin: 0 !important;
}

/* ========================================
   Dropdown: Copy.py風シャープスタイル
   ======================================== */
[data-testid="dropdown"] {
    background: transparent !important;
    border: none !important;
    box-shadow: none !important;
    border-radius: 0 !important;
}
[data-testid="dropdown"] > div,
[data-testid="dropdown"] .wrap,
[data-testid="dropdown"] .wrap-inner,
[data-testid="dropdown"] .secondary-wrap,
[data-testid="dropdown"] input,
[data-testid="dropdown"] .multiselect {
    background: #ffffff !important;
    border: none !important;
    border-radius: 0 !important;
    box-shadow: none !important;
    outline: none !important;
}
[data-testid="dropdown"] .wrap,
[data-testid="dropdown"] .secondary-wrap {
    border: 1px solid #5a7a5a !important;
    box-shadow: 3px 3px 0px 0px #c0d8c0 !important;
    padding: 8px 10px !important;
}
[data-testid="dropdown"] *:not(ul):not(ul *) {
    background: #ffffff !important;
    color: #1a1a1a !important;
    border-radius: 0 !important;
}

ul.options, ul.options li, .options, .options .item,
.secondary-wrap .item, .secondary-wrap ul li {
    background: #2a3a2a !important;
    color: #ffffff !important;
    border-radius: 0 !important;
}
ul.options li:hover, .options .item:hover, .secondary-wrap .item:hover {
    background: #3a4a3a !important;
    color: #ffffff !important;
}

/* ========================================
   Slider: ラグジュアリー仕様
   ======================================== */
input[type="range"] {
    -webkit-appearance: none !important;
    appearance: none !important;
    height: 3px !important;
    background: linear-gradient(90deg,
        #b2d8e8 0%,
        #b2e0d4 50%,
        #c8e8c0 100%) !important;
    border-radius: 0 !important;
    outline: none !important;
    cursor: pointer !important;
    overflow: visible !important;
    margin: 12px 0 !important;
}
input[type="range"]::-webkit-slider-thumb {
    -webkit-appearance: none !important;
    appearance: none !important;
    width: 14px !important;
    height: 14px !important;
    background: #3a5a3a !important;
    border: 1.5px solid #8aaa8a !important;
    border-radius: 0 !important;
    transform: rotate(45deg) !important;
    cursor: pointer !important;
    box-shadow: 2px 2px 4px rgba(0,0,0,0.15) !important;
    margin-top: -6px !important;
    position: relative !important;
}
input[type="range"]::-moz-range-thumb {
    width: 14px !important;
    height: 14px !important;
    background: #3a5a3a !important;
    border: 1.5px solid #8aaa8a !important;
    border-radius: 0 !important;
    transform: rotate(45deg) !important;
    cursor: pointer !important;
}
input[type="range"]::-webkit-slider-runnable-track {
    height: 3px !important;
    background: linear-gradient(90deg,
        #b2d8e8 0%,
        #b2e0d4 50%,
        #c8e8c0 100%) !important;
    border-radius: 0 !important;
    overflow: visible !important;
}

[data-testid="slider"] {
    background: rgba(255,255,255,0.6) !important;
    border: 1.25px solid #a8c8a8 !important;
    border-radius: 0 !important;
    padding: 12px 14px 16px 14px !important;
    box-shadow: 3px 3px 0px 0px #c0d8c0 !important;
    overflow: visible !important;
}
[data-testid="slider"] > div,
[data-testid="slider"] .wrap,
[data-testid="slider"] .wrap-inner {
    overflow: visible !important;
}
[data-testid="slider"] .label-wrap span,
[data-testid="slider"] label span {
    font-family: 'Cormorant Garamond', 'Georgia', serif !important;
    font-size: 11px !important;
    letter-spacing: 0.12em !important;
    text-transform: uppercase !important;
    color: #4a6a4a !important;
}
[data-testid="slider"] button {
    border-radius: 0 !important;
    border: 1.25px solid #a8c8a8 !important;
    background: #f0f5f0 !important;
    padding: 4px 6px !important;
}

/* ========================================
   Radioボタン: ダイヤモンド◆スタイル
   ======================================== */
.diamond-radio,
.diamond-radio *:not(input):not(span) {
    background: transparent !important;
    background-color: transparent !important;
    box-shadow: none !important;
    border-color: transparent !important;
}
.diamond-radio {
    border: 2px solid transparent !important;
    border-image: linear-gradient(135deg, #b2d8e8 0%, #b2e0d4 50%, #c8e8c0 100%) 1 !important;
    border-radius: 0 !important;
    padding: 12px 14px !important;
}
.diamond-radio label,
.diamond-radio .wrap label,
.diamond-radio label.svelte-1kcyvh9 {
    display: flex !important;
    align-items: center !important;
    gap: 10px !important;
    padding: 10px 12px !important;
    cursor: pointer !important;
    transition: all 0.2s ease !important;
    border-bottom: 1px solid rgba(138,170,138,0.15) !important;
    font-family: 'Cormorant Garamond', 'Georgia', serif !important;
    font-size: 14px !important;
    font-weight: 500 !important;
    letter-spacing: 0.08em !important;
}
.diamond-radio label:last-child {
    border-bottom: none !important;
}
.diamond-radio label:hover {
    background: rgba(178,216,210,0.15) !important;
}
/* ラジオ丸→ダイヤモンド: あらゆるinput[type=radio]をカバー */
.diamond-radio input[type="radio"],
.diamond-radio input[type="radio"]::before,
.diamond-radio input[type="radio"]::after {
    -webkit-appearance: none !important;
    appearance: none !important;
    border-radius: 0 !important;
}
.diamond-radio input[type="radio"] {
    width: 14px !important;
    height: 14px !important;
    min-width: 14px !important;
    border: 1.5px solid #8aaa8a !important;
    background: #ffffff !important;
    transform: rotate(45deg) !important;
    cursor: pointer !important;
    transition: all 0.25s ease !important;
    box-shadow: 1px 1px 3px rgba(0,0,0,0.1) !important;
    margin: 0 4px 0 0 !important;
    padding: 0 !important;
    flex-shrink: 0 !important;
}
.diamond-radio input[type="radio"]:checked {
    background: linear-gradient(135deg, #a0cfe0 0%, #90d4c8 50%, #b0e0a0 100%) !important;
    border-color: #7abaa0 !important;
    box-shadow: 2px 2px 4px rgba(0,0,0,0.2) !important;
}
/* Gradio 6: 丸いsvg/spanインジケーターも上書き */
.diamond-radio .radio-circle,
.diamond-radio [class*="radio"] span:first-child,
.diamond-radio .item > div:first-child,
.diamond-radio .choice > div:first-child {
    width: 14px !important;
    height: 14px !important;
    min-width: 14px !important;
    border: 1.5px solid #8aaa8a !important;
    border-radius: 0 !important;
    background: #ffffff !important;
    transform: rotate(45deg) !important;
    box-shadow: 1px 1px 3px rgba(0,0,0,0.1) !important;
    transition: all 0.25s ease !important;
}
.diamond-radio .selected .radio-circle,
.diamond-radio .selected [class*="radio"] span:first-child,
.diamond-radio .selected .item > div:first-child,
.diamond-radio .selected .choice > div:first-child {
    background: linear-gradient(135deg, #a0cfe0 0%, #90d4c8 50%, #b0e0a0 100%) !important;
    border-color: #7abaa0 !important;
    box-shadow: 2px 2px 4px rgba(0,0,0,0.2) !important;
}

/* ========================================
   Gradioボタン: VIEW MORE風 / セリフ体 / シャープ
   ======================================== */
button[class*="primary"], button[class*="secondary"],
button.lg {
    border-radius: 0 !important;
    font-family: 'Cormorant Garamond', 'Georgia', 'Times New Roman', 'YuMincho', serif !important;
    font-weight: 500 !important;
    font-size: 13px !important;
    letter-spacing: 0.18em !important;
    text-transform: uppercase !important;
    padding: 15px 24px !important;
    transition: all 0.3s ease !important;
    touch-action: manipulation !important;
    -webkit-tap-highlight-color: transparent !important;
}

/* Primary: ダーク背景 */
button[class*="primary"] {
    background: #3a5a3a !important;
    color: #d8e8d8 !important;
    border: 1px solid #3a5a3a !important;
    box-shadow: none !important;
}
button[class*="primary"]:hover {
    background: #4a6a4a !important;
}
button[class*="primary"]:active {
    background: #5a7a5a !important;
}

/* Secondary: 白背景 + 細線ボーダー */
button[class*="secondary"] {
    background: #ffffff !important;
    color: #4a5a4a !important;
    border: 1px solid #8aaa8a !important;
    box-shadow: none !important;
}
button[class*="secondary"]:hover {
    background: #f5faf5 !important;
    border-color: #6a8a6a !important;
}
button[class*="secondary"]:active {
    background: #eef5ee !important;
}

/* ========================================
   Textbox / Markdown
   ======================================== */
textarea {
    background: rgba(255,255,255,0.7) !important;
    color: #1a1a1a !important;
    border-radius: 0 !important;
    border: 1px solid #a8c8a8 !important;
    font-family: 'SF Mono', 'Fira Code', ui-monospace, monospace !important;
    font-size: 12px !important;
}

.prose, .markdown-text, .md {
    color: #1a1a1a !important;
}
.prose h2, .prose h3 {
    font-family: 'Cormorant Garamond', 'Georgia', 'Times New Roman', serif !important;
    color: #2a3a2a !important;
    font-weight: 400 !important;
    letter-spacing: 0.08em !important;
}

/* ========================================
   JSON表示
   ======================================== */
.json-holder, [data-testid="json"] {
    background: rgba(255,255,255,0.5) !important;
    border-radius: 0 !important;
    border: 1px solid rgba(138,170,138,0.2) !important;
}

/* ========================================
   Dataframe
   ======================================== */
.dataframe, table {
    border-radius: 0 !important;
}
.dataframe th {
    background: rgba(178,216,210,0.2) !important;
    font-family: 'Cormorant Garamond', 'Georgia', serif !important;
    font-weight: 500 !important;
    letter-spacing: 0.06em !important;
}

/* ========================================
   Audio コンポーネント
   ======================================== */
.audio-container, [data-testid="audio"] {
    border-radius: 0 !important;
    border: 1px solid #a8c8a8 !important;
}

/* ========================================
   Label (確率表示)
   ======================================== */
[data-testid="label"] {
    border-radius: 0 !important;
}

/* ========================================
   セクションタイトル
   ======================================== */
.section-title {
    text-align: center !important;
    padding: 8px 16px !important;
}
.section-title h3 {
    font-family: 'Cormorant Garamond', 'Georgia', 'Times New Roman', serif !important;
    font-size: clamp(13px, 3.5vw, 16px) !important;
    font-weight: 400 !important;
    color: #4a6a4a !important;
    letter-spacing: 0.15em !important;
    text-transform: uppercase !important;
    margin: 0 !important;
}

/* ========================================
   アニメーション
   ======================================== */
@keyframes softFadeIn {
    from { opacity: 0; transform: translateY(12px); }
    to   { opacity: 1; transform: translateY(0); }
}

/* ========================================
   自動録音: ステータス表示
   ======================================== */
.rec-status {
    text-align: center;
    padding: 8px 12px;
    font-family: 'Cormorant Garamond', 'Georgia', serif;
    font-size: 14px;
    color: #4a6a4a;
    letter-spacing: 0.06em;
}
@keyframes recPulse {
    0%, 100% { opacity: 1; }
    50% { opacity: 0.6; }
}

/* ========================================
   スクロールバー
   ======================================== */
::-webkit-scrollbar { width: 4px; }
::-webkit-scrollbar-track { background: transparent; }
::-webkit-scrollbar-thumb {
    background: rgba(138,170,138,0.3);
    border-radius: 4px;
}

/* ========================================
   Gradio内部padding/border補正
   ======================================== */
.block {
    border: none !important;
    background: transparent !important;
    padding: 0 !important;
}
.form {
    background: transparent !important;
    border: none !important;
}
.container {
    background: transparent !important;
}
.tabs {
    background: transparent !important;
}

/* ========================================
   テキスト色: 全体黒、Primaryボタンのみ白
   ======================================== */
* {
    color: #1a1a1a;
}
button[class*="primary"],
button[class*="primary"] * {
    color: #ffffff !important;
}

/* ========================================
   レスポンシブ: PC = 中央固定幅
   ======================================== */
@media (min-width: 768px) {
    .gradio-container > .main,
    .gradio-container > div > .main {
        max-width: 520px !important;
        margin: 0 auto !important;
    }
    .tabitem > div {
        margin: 16px auto 28px auto !important;
        max-width: 480px !important;
    }
    div.tab-nav {
        max-width: 480px !important;
        margin: 16px auto 20px auto !important;
    }
}

/* ========================================
   スマホ特化
   ======================================== */
@media (max-width: 767px) {
    div.tab-nav {
        margin: 12px 12px 16px 12px !important;
        padding: 4px !important;
    }
    div.tab-nav button {
        padding: 9px 10px !important;
        font-size: 12px !important;
    }
    .tabitem > div {
        margin: 12px 12px 24px 12px !important;
        padding: 24px 14px !important;
        box-shadow: 6px 6px 0px 0px #c0d8c0 !important;
    }
    button[class*="primary"], button[class*="secondary"],
    button.lg {
        width: 100% !important;
        padding: 14px 18px !important;
        font-size: 14px !important;
    }
    label span, .label-wrap span {
        font-size: 12px !important;
    }
    input[type="text"], input[type="number"], textarea, select {
        font-size: 16px !important;
    }
}
"""

with gr.Blocks() as demo:

    # ヒーローセクション + リセットボタン
    gr.HTML("""
    <div class="hero-section">
        <h1>Sound Classify</h1>
        <p>Streaming ESN &#183; Record &#183; Learn &#183; Predict</p>
    </div>
    """)
    reset_btn = gr.Button("Reset All", size="sm")

    with gr.Tabs():

        # ── 収集タブ(ラベル管理 + 録音 + データ一覧を統合) ──
        with gr.Tab("収集"):
            # ラベル追加
            gr.Markdown("### ラベル追加")
            with gr.Row():
                label_box = gr.Textbox(label="新ラベル", placeholder="例: yes", scale=3)
                add_btn = gr.Button("追加", size="lg", scale=1)

            # 録音 & サンプル追加(自動停止)
            gr.Markdown("### 録音(自動停止)")
            label_dd = gr.Radio(choices=LABELS, label="ラベル選択", interactive=True, elem_classes=["diamond-radio"])
            with gr.Column(elem_id="auto_rec_area"):
                audio_rec = gr.Audio(sources=["microphone"], type="numpy", label="マイク(録音→自動停止→自動保存)")
                gr.HTML('<div id="rec_status_js" class="rec-status">待機中... 録音ボタンを押してください</div>')
            rec_status_md = gr.Markdown("", elem_classes=["rec-status"])
            undo_btn = gr.Button("Undo", size="lg")

            # データ一覧 & 編集
            gr.Markdown("### データ一覧")
            table = gr.Dataframe(
                headers=["idx", "label", "sec"],
                value=dataset_table(),
                datatype=["number", "str", "number"],
                row_count=(6, "dynamic"),
                column_count=(3, "fixed"),
                interactive=False,
                elem_id="data_table"
            )
            selected_idx_state = gr.State(None)
            replay_audio = gr.Audio(type="numpy", label="選択した音声(再生)", interactive=False)
            relabel_dd = gr.Radio(choices=LABELS, label="ラベル修正", interactive=True, elem_classes=["diamond-radio"])
            with gr.Row():
                relabel_btn = gr.Button("ラベル更新", size="lg")
                del_btn = gr.Button("削除", size="lg")

        # ── 学習タブ ──
        with gr.Tab("学習"):
            trials = gr.Slider(3, 30, value=8, step=1, label="Trials")
            train_btn = gr.Button("学習", variant="primary", size="lg")
            train_log = gr.Textbox(label="学習ログ", interactive=False, lines=2)

        # ── 推論タブ ──
        with gr.Tab("推論"):
            stream_audio = gr.Audio(sources=["microphone"], streaming=True, type="numpy", label="入力")
            st = gr.State(None)
            pred_box = gr.Textbox(label="推定", interactive=False)
            prob_box = gr.Label(label="確率", num_top_classes=10)
            stream_audio.stream(stream_predict, inputs=[stream_audio, st], outputs=[pred_box, prob_box, st])

    # wiring
    add_btn.click(add_label_cb, inputs=[label_box], outputs=[label_dd, table, relabel_dd])
    undo_btn.click(undo_last_cb, inputs=[], outputs=[table])
    reset_btn.click(reset_all_cb, inputs=[], outputs=[table, label_dd, relabel_dd, audio_rec, selected_idx_state])

    # 録音完了時に自動保存(stop_recording = 停止ボタン押下)
    audio_rec.stop_recording(auto_add_sample_cb, inputs=[audio_rec, label_dd], outputs=[table, audio_rec, rec_status_md])

    # select row -> update state + replay + relabel dropdown value
    def _select_and_store(evt: gr.SelectData):
        if evt is None or evt.index is None:
            return None, None, gr.update(value=None)
        row = evt.index[0] if isinstance(evt.index, (tuple, list)) else int(evt.index)
        if row < 0 or row >= len(DATA):
            return None, None, gr.update(value=None)
        item = DATA[row]
        return row, item["audio"], gr.update(value=item["label"])

    table.select(_select_and_store, inputs=None, outputs=[selected_idx_state, replay_audio, relabel_dd])

    relabel_btn.click(relabel_selected_cb, inputs=[selected_idx_state, relabel_dd], outputs=[table])
    del_btn.click(delete_selected_cb, inputs=[selected_idx_state], outputs=[table, selected_idx_state, relabel_dd])

    train_btn.click(train_random, inputs=[trials], outputs=[train_log])
if __name__ == "__main__":
    demo.launch(
        server_name="0.0.0.0",
        server_port=7860,
        css=CSS,
        head=HEAD,
        theme=gr.themes.Base(
            text_size=gr.themes.sizes.text_md,
            font=[gr.themes.GoogleFont("Inter"), gr.themes.GoogleFont("Noto Sans JP")],
        ).set(
            body_text_color="#1a1a1a",
            body_text_color_subdued="#4a5a4a",
            block_label_text_color="#2a3a2a",
            block_title_text_color="#1a1a1a",
            checkbox_label_text_color="#1a1a1a",
            table_text_color="#1a1a1a",
            link_text_color="#3a5a3a",
            color_accent_soft="#c8e0d0",
            input_background_fill="#ffffff",
            input_background_fill_dark="#ffffff",
            input_border_color="#8aaa8a",
            input_border_color_dark="#8aaa8a",
        ),
    )