Search Results for "dtmf decoder python"
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25 projects for "dtmf decoder python" with 1 filter applied:
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FusionAuth: Authentication and User Management SoftwareFusionAuth adds login, registration, SSO, MFA, and a bazillion other features to your app in days - not months.
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Save up to 90% off rates for USPS, UPS, DHL Express, and more with the best multi-carrier shipping software for e-commerce businesses.Whether you're established or just getting started, Shippo is the best shipping software for growing e-commerce brands that need to save time and money, fulfill and ship at scale, and delight customers. Create shipping labels for all carriers & save money with discounted rates. See all your online sales channels in one place and automatically access discounted USPS and DHL Express rates, or use your own carrier accounts. Sign up is free and there are no monthly fees or cancellation fees.
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Whisper
Robust Speech Recognition via Large-Scale Weak Supervision
OpenAI Whisper is a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multitasking model that can perform multilingual speech recognition, speech translation, and language identification. A Transformer sequence-to-sequence model is trained on various speech processing tasks, including multilingual speech recognition, speech translation, spoken language identification, and voice activity detection. These tasks are jointly represented... -
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Segment Anything
Provides code for running inference with the SegmentAnything Model
...It’s a promptable segmenter: you guide it with points, boxes, or rough masks, and it predicts high-quality object masks consistent with the prompt. The architecture separates a powerful image encoder from a lightweight mask decoder, so the heavy vision work can be computed once and the interactive part stays fast. A bundled automatic mask generator can sweep an image and propose many object masks, which is useful for dataset bootstrapping or bulk annotation. The repository includes ready-to-use weights, Python APIs, and example notebooks demonstrating both interactive and automatic modes. ... -
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Kronos
A Foundation Model for the Language of Financial Markets
Kronos is a specialized open-source foundation model designed for analyzing and predicting financial market data using time-series representations of candlestick patterns. It is built as a decoder-only Transformer model trained specifically on K-line data, which captures open, high, low, close, and volume information across multiple global exchanges. The system introduces a novel tokenization approach that converts continuous financial data into discrete tokens, enabling the model to process... -
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GLM-OCR
Accurate × Fast × Comprehensive
GLM-OCR is an open-source multimodal optical character recognition (OCR) model built on a GLM-V encoder–decoder foundation that brings robust, accurate document understanding to complex real-world layouts and modalities. Designed to handle text recognition, table parsing, formula extraction, and general information retrieval from documents containing mixed content, GLM-OCR excels across major benchmarks while remaining highly efficient with a relatively compact parameter size (~0.9B),... -
Assembled is the only unified platform for staffing and managing your human and AI support team.Assembled is the only platform that unifies AI agents and intelligent workforce management to power fast and flexible support operations. Built for scale, we help teams automate over 50% of customer interactions, forecast with 90%+ accuracy, and optimize staffing across in-house and BPO teams. Orchestrate every chat, email, or call, balancing workloads between human and AI agents in real time — without sacrificing quality or control. Trusted by Stripe, Canva, and Robinhood, Assembled transforms support from a cost center into a strategic advantage. Our Workforce and Vendor Management tools connect forecasting, scheduling, and performance for smarter staffing decisions. AI Agents automate conversations across channels with your workflows and brand voice. AI Copilot empowers agents with real-time guidance, suggested replies, and one-click actions for faster, higher-quality resolutions.
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IndexTTS2
Industrial-level controllable zero-shot text-to-speech system
IndexTTS is a modern, zero-shot text-to-speech (TTS) system engineered to deliver high-quality, natural-sounding speech synthesis with few requirements and strong voice-cloning capabilities. It builds on state-of-the-art models such as XTTS and other modern neural TTS backbones, improving them with a conformer-based speech conditional encoder and upgrading the decoder to a high-quality vocoder (BigVGAN2), leading to clearer and more natural audio output. The system supports zero-shot voice... -
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ESPnet
End-to-end speech processing toolkit
ESPnet is a comprehensive end-to-end speech processing toolkit covering a wide spectrum of tasks, including automatic speech recognition (ASR), text-to-speech (TTS), speech translation (ST), speech enhancement, speaker diarization, and spoken language understanding. It uses PyTorch as its deep learning engine and adopts a Kaldi-style data processing pipeline for features, data formats, and experimental recipes. This combination allows researchers to leverage modern neural architectures while... -
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TimesFM
Pretrained time-series foundation model developed by Google Research
TimesFM is a pretrained time-series foundation model from Google Research built for forecasting tasks, designed to generalize across many domains without requiring extensive per-dataset retraining. It provides a decoder-only model approach to forecasting, aiming for strong performance even in zero-shot or low-data settings where traditional models often struggle. The project includes code and an inference API intended to make it practical to run forecasts programmatically, with options to... -
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Multimodal
TorchMultimodal is a PyTorch library
This project, also known as TorchMultimodal, is a PyTorch library for building, training, and experimenting with multimodal, multi-task models at scale. The library provides modular building blocks such as encoders, fusion modules, loss functions, and transformations that support combining modalities (vision, text, audio, etc.) in unified architectures. It includes a collection of ready model classes—like ALBEF, CLIP, BLIP-2, COCA, FLAVA, MDETR, and Omnivore—that serve as reference... -
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AV1 AVIF
AV1 Image File Format Specification - ISO-BMFF/HEIF derivative
AV1 AVIF is the official specification and reference design for the AV1 Image File Format (AVIF), defining how AV1-encoded bitstreams are packaged into the HEIF container format (based on ISOBMFF) to produce AVIF files. The project outlines the syntax and semantics required for AVIF compliance, including support for multiple image profiles, color depths, chroma subsampling modes, HDR/WCG, alpha channels, animation/image sequences, and various color-space/bit-depth combinations — making AVIF... -
GoAnywhere Managed File Transfer (MFT)GoAnywhere MFT provides secure managed file transfer for enterprises. Deployable on-premise, in the cloud, or in hybrid environments, GoAnywhere MFT software enables organizations to exchange data among employees, customers, and trading partners, as well as between systems, securely. GoAnywhere MFT was a recipient of the Cybersecurity Excellence Award for Secure File Transfer.
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CSM (Conversational Speech Model)
A Conversational Speech Generation Model
The CSM (Conversational Speech Model) is a speech generation model developed by Sesame AI that creates RVQ audio codes from text and audio inputs. It uses a Llama backbone and a smaller audio decoder to produce audio codes for realistic speech synthesis. The model has been fine-tuned for interactive voice demos and is hosted on platforms like Hugging Face for testing. CSM offers a flexible setup and is compatible with CUDA-enabled GPUs for efficient execution. -
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iced
Blazing fast and correct x86/x64 disassembler, assembler, decoder, etc
iced is a powerful and feature-rich disassembly and assembly library for x86 and x64 architectures, designed to provide accurate decoding, encoding, and formatting of machine instructions. It supports multiple programming languages, including C#, Rust, and Python, making it accessible to a wide range of developers. The library offers both disassembly and assembly capabilities, allowing users to convert between machine code and human-readable instructions in both directions. It includes... -
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DiffSinger
Singing Voice Synthesis via Shallow Diffusion Mechanism
DiffSinger is an open-source PyTorch implementation of a diffusion-based acoustic model for singing-voice synthesis (SVS) and also text-to-speech (TTS) in a related variant. The core idea is to view generation of a sung voice (mel-spectrogram) as a diffusion process: starting from noise, the model iteratively “denoises” while being conditioned on a music score (lyrics, pitch, musical timing). This avoids some of the typical problems of prior SVS models — like over-smoothing or unstable GAN... -
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Mask2Former
Code release for "Masked-attention Mask Transformer
Mask2Former is a unified segmentation architecture that handles semantic, instance, and panoptic segmentation with one model and one training recipe. Its core idea is to cast segmentation as mask classification: a transformer decoder predicts a set of mask queries, each with an associated class score, eliminating the need for task-specific heads. A pixel decoder fuses multi-scale features and feeds masked attention in the transformer so each query focuses computation on its current spatial... -
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MAE (Masked Autoencoders)
PyTorch implementation of MAE
MAE (Masked Autoencoders) is a self-supervised learning framework for visual representation learning using masked image modeling. It trains a Vision Transformer (ViT) by randomly masking a high percentage of image patches (typically 75%) and reconstructing the missing content from the remaining visible patches. This forces the model to learn semantic structure and global context without supervision. The encoder processes only the visible patches, while a lightweight decoder reconstructs the... -
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Denoiser
Real Time Speech Enhancement in the Waveform Domain (Interspeech 2020)
Denoiser is a real-time speech enhancement model operating directly on raw waveforms, designed to clean noisy audio while running efficiently on CPU. It uses a causal encoder-decoder architecture with skip connections, optimized with losses defined both in the time domain and frequency domain to better suppress noise while preserving speech. Unlike models that operate on spectrograms alone, this design enables lower latency and coherent waveform output. The implementation includes data... -
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ALAE
Adversarial Latent Autoencoders
ALAE (Adversarial Latent Autoencoders) is a deep learning research implementation that combines autoencoders with generative adversarial networks to produce high-quality image synthesis models. The project implements the architecture introduced in the CVPR research paper on Adversarial Latent Autoencoders, which focuses on improving generative modeling by learning latent representations aligned with adversarial training objectives. Unlike traditional GANs that directly generate images from... -
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OpenSeq2Seq
Toolkit for efficient experimentation with Speech Recognition
OpenSeq2Seq is a TensorFlow-based toolkit for efficient experimentation with sequence-to-sequence models across speech and NLP tasks. Its core goal is to give researchers a flexible, modular framework for building and training encoder–decoder architectures while fully leveraging distributed and mixed-precision training. The toolkit includes ready-made models for neural machine translation, automatic speech recognition, speech synthesis, language modeling, and additional NLP tasks such as... -
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seq2seq
A general-purpose encoder-decoder framework for Tensorflow
seq2seq is an early, influential TensorFlow reference implementation for sequence-to-sequence learning with attention, covering tasks like neural machine translation, summarization, and dialogue. It packaged encoders, decoders, attention mechanisms, and beam search into a modular training and inference framework. The codebase showcased best practices for batching, bucketing by sequence length, and handling variable-length sequences efficiently on GPUs. Researchers used it as a baseline to... -
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toneDetect
toneDetect
A sequential tone decoder geared towards the type of paging used by Fire/EMS. It is written in Python for portability and has been tested on Windows, Linux and Mac. It provides email notification of pages which includes the audio. -
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DTMF detector library and/or application that reads in the specified audio file and returns/outputs whether DTMF detected and/or list of detected digits. May have GUI and command line interfaces.
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Tool for encoding tags of mp3 files in the cyrillic charsets (cp1251, koi8-r) to unicode. Solution of problem with displaying tags in thе different charsets in a playlist. If you will find bug, mistake in the this text - mail me on hlamer@tut.by
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Python wrapper for LibSSH2 and OpenSSL libraries. Includes: yEnc (coder, decoder), hunspell, Par2, crc64
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