A Tool Website Developed with Python
This article introduces a feature-rich tool website developed using Python. It includes various tools such as document tools, PDF tools, image tools, audio tools, video tools, voice tools, and programming tools, which are commonly used in work or study.
Read MoreSpeaker Log Implementation Based on PyTorch (Speaker Separation)
This article introduces the speaker diarization feature of the VoiceprintRecognition_Pytorch framework implemented based on PyTorch, which supports various advanced models and data preprocessing methods. By executing the `infer_speaker_diarization.py` script or using the GUI interface program, audio can be speaker-separated and results displayed. The output includes the start and end times of each speaker and their identity information (registration is required first). Additionally, the article provides solutions for Chinese names in the Ubuntu system... （注：原文末尾“解决中文名”表述不完整，已保留原文未尽部分的省略格式，完整内容需参考原文后续章节）
Read MoreIntroduction and Usage of YeAudio Audio Tool
These classes define various audio data augmentation techniques. Each class is responsible for a specific data augmentation operation and can control the degree and type of augmentation by setting different parameters. The following is a detailed description of each class: ### 1. **SpecAugmentor** - **Function**: Frequency domain masking and time domain masking - **Main Parameters**: - `prob`: Probability of data augmentation. - `freq_mask_ratio`: Ratio of frequency domain masking (e.g., 0.15 means randomly selecting
Read MoreVoiceprint Recognition System Implemented Based on PyTorch
This project provides an implementation of voice recognition based on PaddlePaddle, mainly using the EcapaTDNN model, and integrates functions of speech recognition and voiceprint recognition. Below, I will summarize the project structure, functions, and how to use these functions. ## Project Structure ### Directory Structure ``` VoiceprintRecognition-PaddlePaddle/ ├── docs/ # Documentation │ └── README.md # Project description document ```
Read MoreSegmenting Long Speech into Multiple Short Segments Using Voice Activity Detection (VAD)
This paper introduces YeAudio, a voice activity detection (VAD) tool implemented based on deep learning. The installation command for the library is `python -m pip install yeaudio -i https://pypi.tuna.tsinghua.edu.cn/simple -U`, and the following code snippet can be used for speech segmentation: ```python from yeaaudio.audio import AudioSegment audio_seg ``` (Note: The original code snippet appears incomplete in the user's input; the translation preserves the partial code as provided.)
Read MoreECAPa-TDNN Speaker Recognition Model Implemented Based on PaddlePaddle
This project is a voiceprint recognition system based on PaddlePaddle. It covers application scenarios from data preprocessing, model training to voiceprint recognition and comparison, and is suitable for practical applications such as voiceprint login. Here is a detailed analysis of the project: ### 1. Environment Preparation and Dependency Installation First, ensure that PaddlePaddle and other dependent libraries such as `numpy`, `matplotlib`, etc., have been installed. They can be installed using the following command: ```bash pip install paddlepaddle ```
Read MoreAdding Punctuation Marks to Speech Recognition Text
This paper introduces a method for adding punctuation marks to speech recognition text according to grammar, mainly divided into four steps: downloading and decompressing the model, installing PaddleNLP and PPASR tools, importing the PunctuationPredictor class, and using this class to automatically add punctuation marks to the text. The specific steps are as follows: 1. Download the model and decompress it into the `models/` directory. 2. Install the relevant libraries of PaddleNLP and PPASR. 3. Instantiate the predictor using the `PunctuationPredictor` class and pass in the pre
Read MoreSound Classification Based on PyTorch
This code is mainly based on the PaddlePaddle framework and is used to implement a speech recognition system based on acoustic features. The project structure is clear, including functional modules such as training, evaluation, and prediction, and provides detailed command-line parameter configuration files. The following is a detailed analysis and usage instructions for the project: ### 1. Project Structure ``` . ├── configs # Configuration files directory │ └── bi_lstm.yml ├── infer.py # Acoustic model inference code ├── recor ``` (Note: The original Chinese text was cut off at "recor" in the last line, so the translation reflects the visible content.)
Read MoreImplementing Common Sorting Algorithms in Python
Thank you very much for sharing the implementations of these sorting algorithms. To provide a more comprehensive and understandable version, I will briefly explain each sorting algorithm and include complete code snippets. Additionally, I will add necessary import statements and comments within each function to enhance code readability. ### 1. Bubble Sort Bubble Sort is a simple sorting method that repeatedly traverses the list to be sorted, comparing two elements at a time and swapping them if their order is incorrect. After multiple traversals, the largest element "bubbles up" to the end. ```python def bubble_sort(arr): n = len(arr) for i in range(n): # Last i elements are already in place swapped = False for j in range(0, n-i-1): if arr[j] > arr[j+1]: arr[j], arr[j+1] = arr[j+1], arr[j] swapped = True # If no swaps occurred, the array is sorted if not swapped: break return arr ```
Read MoreDistance Measurement Using Binocular Cameras
This code demonstrates how to implement stereo vision depth estimation using the SGBM (Semiglobal Block Matching) algorithm in OpenCV, and then calculate 3D coordinates in the image. The following is a detailed explanation of the key steps and parameters in the code: ### 1. Preparation First, import the necessary libraries: ```python import cv2 import numpy as np ``` ### 2. Reading and Preprocessing Images Load the left and right eye images, and then (the original content was cut off here, so the translation stops at the beginning of the preprocessing step)
Read MoreImplementing a Simple Web Crawler with Python2
This project is a simple web crawler designed to scrape relevant content from CSDN blogs and save it as HTML files. It includes the basic process of a crawler: crawling, parsing, and storage. ### Crawling Process 1. **Scheduler (`spider_main.py`)**: - This is the entry point of the entire project. - It calls `HtmlOutputer` to output data, `Downloader` to download web page content, and `HtmlParser` to parse the downloaded content (parsing logic continues...).
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