Nguyen Hong Duc ducnh1022

## gist:606a1821836e14de6555dda98a31bf9c
import difflib

def fuzzy_insert(words, new_word, threshold=0.6):
    # 1️⃣ Calculate similarity scores
    similarities = [
        (i, difflib.SequenceMatcher(None, new_word, w).ratio())
        for i, w in enumerate(words)
    ]

    # 2️⃣ Find best match

## gist:701b48cc874a2a617d227ef7b4697413
import torch
import torchaudio
import numpy as np
import soundfile as sf
from speechbrain.pretrained import SpeakerRecognition
from scipy.spatial.distance import cosine


# ============================
# CONFIG

## gist:72585412f4b3dd06da5a895da2add58d
import sounddevice as sd
import soundfile as sf
import numpy as np
import queue
import datetime
import os

# ==============================
# CONFIG
# ==============================

## gist:06355de13df1975f8decbc57951f1b9e
import webrtcvad
import collections
import sys
import wave
import contextlib
from pydub import AudioSegment


def read_wave(path):
    with contextlib.closing(wave.open(path, 'rb')) as wf:

## gist:51848345be0d4defcb65b40ddbb76e1c
import collections
import sys
import wave
import time
import webrtcvad
import pyaudio

# Audio settings
FORMAT = pyaudio.paInt16
CHANNELS = 1

## gist:23d2f1f70c221bed4104287b99732e8e
# Most compatible way – use .loc / .iat if DataFrame, indexing if ndarray
        loudness = float(features['loudness_sma3_amean'].item()
                        if hasattr(features, '__getitem__') and 'loudness_sma3_amean' in features
                        else features[smile.feature_names.index('loudness_sma3_amean')])

        voicing_key = 'voicingProb_sma3nz_amean'
        voicing = 0.0
        if voicing_key in smile.feature_names:
            idx = smile.feature_names.index(voicing_key)
            voicing = float(features[voicing_key].item()

## gist:2481f4acbf53d737cffc09298dbec338
import pyaudio
import numpy as np
import opensmile
import time
import datetime
import collections
import soundfile as sf   # pip install soundfile

# ================= Configuration =================
SAMPLE_RATE = 16000

## game_hanzi.html
<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>VerbVibe - Trilingual Master</title>
    <link href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&display=swap" rel="stylesheet">
    <style>
        :root {
            --primary-blue: #A2D2FF;
	import difflib

	def fuzzy_insert(words, new_word, threshold=0.6):
	# 1️⃣ Calculate similarity scores
	similarities = [
	(i, difflib.SequenceMatcher(None, new_word, w).ratio())
	for i, w in enumerate(words)
	]

	# 2️⃣ Find best match
	import torch
	import torchaudio
	import numpy as np
	import soundfile as sf
	from speechbrain.pretrained import SpeakerRecognition
	from scipy.spatial.distance import cosine


	# ============================
	# CONFIG
	import sounddevice as sd
	import soundfile as sf
	import numpy as np
	import queue
	import datetime
	import os

	# ==============================
	# CONFIG
	# ==============================
	import webrtcvad
	import collections
	import sys
	import wave
	import contextlib
	from pydub import AudioSegment


	def read_wave(path):
	with contextlib.closing(wave.open(path, 'rb')) as wf:
	# Most compatible way – use .loc / .iat if DataFrame, indexing if ndarray
	loudness = float(features['loudness_sma3_amean'].item()
	if hasattr(features, '__getitem__') and 'loudness_sma3_amean' in features
	else features[smile.feature_names.index('loudness_sma3_amean')])

	voicing_key = 'voicingProb_sma3nz_amean'
	voicing = 0.0
	if voicing_key in smile.feature_names:
	idx = smile.feature_names.index(voicing_key)
	voicing = float(features[voicing_key].item()
	import pyaudio
	import numpy as np
	import opensmile
	import time
	import datetime
	import collections
	import soundfile as sf # pip install soundfile

	# ================= Configuration =================
	SAMPLE_RATE = 16000
	<!DOCTYPE html>
	<html lang="en">
	<head>
	<meta charset="UTF-8">
	<meta name="viewport" content="width=device-width, initial-scale=1.0">
	<title>VerbVibe - Trilingual Master</title>
	<link href="https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&display=swap" rel="stylesheet">
	<style>
	:root {
	--primary-blue: #A2D2FF;