Even if a project is deleted, the ID can never be used again. To clean HTML pages you can try BoilerPipe. Jetsonian Age, separate page about large scale Logical and Physical Line; The Python Language Reference. It offers a persistent 5GB home directory and runs in Google Cloud, greatly enhancing network performance and authentication. If you use PyKaldi for research, please cite our paper as Please refer to the tutorial page for complete documentation. The list shows 53 languages and variants such as: This list is not fixed and will grow as new voices are available. Running the commands below will install the system packages needed for building trees in Kaldi, check out the gmm, sgmm2, hmm, and tree While Google Cloud can be operated remotely from your laptop, in this tutorial you will be using Cloud Shell, a command line environment running in the Cloud. Make sure you activate the new Python environment before continuing with the The corpus is just a list of sentences that you will use to train the Please access the notebook from the following button and enjoy the real-time speech-to-speech translation! Customizable speech-specific sentence tokenizer that allows for unlimited lengths of text to be read, all while keeping proper intonation, abbreviations, decimals and more; Customizable text pre-processors which can, for example, provide pronunciation corrections. In the meantime, you can also use the unofficial whl builds for Python 3.9 from Uni-Hamburgs pykaldi repo. Ignoring the We have passed. If you are interested in using PyKaldi for research or building advanced ASR It is very easy to use the tool and provides many built-in functions which used to save the text file as an mp3 file. This project is not affiliated with Google or Google Cloud. We pack the MFCC features and the i-vectors into a Like Kaldi, PyKaldi is primarily intended for speech recognition researchers and If you do not Language Understanding Service(LUIS) allows your application to understand what a person wants in their own words. Python modules grouping together related extension modules generated with CLIF Sign up for the Google Developers newsletter, modulating the output in pitch, volume, speaking rate, and sample rate, https://cloud.google.com/text-to-speech/docs, https://googlecloudplatform.github.io/google-cloud-python, How to install the client library for Python, For your information, there is a third value, a. For this, set the gratis_blank option that allows skipping unrelated audio sections without penalty. You signed in with another tab or window. To align utterances: The output of the script can be redirected to a segments file by adding the argument --output segments. You can dimensions: If you are using a relatively recent Linux or macOS, such as Ubuntu >= 16.04, With the Bot Framework SDK, developers can build bots that converse free-form or with guided interactions including using simple text or rich cards that contain text, images, and action buttons. public APIs of Kaldi and OpenFst C++ libraries. Write spoken mp3 data to a file, a file-like object (bytestring) for further audio manipulation, or stdout . ), Supports using context from previous utterances, Supports using other tasks like SE in pipeline manner, Supports Two Pass SLU that combines audio and ASR transcript and speaker adaptation. word features and the feature embeddings on the fly. You can find almost every language in this library. Tortoise is primarily an autoregressive decoder model combined with a diffusion model. If your keyphrase is very Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. You can produce Use Git or checkout with SVN using the web URL. PyKaldi from source. If you're experiencing stuttering in the audio try to increase this number. model in your Configuration: If the model is in the resources you can reference it with "resource:URL": Also see the Sphinx4 tutorial for more details. We made a new real-time E2E-ST + TTS demonstration in Google Colab. Speech Recognition and Other Exotic User Interfaces at the Twilight of the Now, we can hear the text file in the voices. tags. Create the main window (container) Add any number of widgets to the main window. model. no easy task. You signed in with another tab or window. implementing new Kaldi tools. audio file. To create a tkinter application: Importing the module tkinter. The audio sample is gathered by the means of listening to the method in the recognizer class. boilerplate code needed for setting things up, doing ASR with PyKaldi can be as Please download and enjoy the generation of high quality speech! language model and dictionary are called 8521.dic and 8521.lm and It also provides some additional properties that we can use according to our needs. for parts separately. You can configure the output of speech synthesis in a variety of ways, including selecting a unique voice or modulating the output in pitch, volume, speaking rate, and sample rate. You can find useful tutorials and demos in Interspeech 2019 Tutorial. same as for English, with one additional consideration. Quickly create enterprise-ready, custom models that continuously improve. In Python you can either specify options in the configuration object or add a Creating the conversion methods. Please click the following button to get access to the demos. [Docs]. the nnet3, cudamatrix and chain packages. Caution: A project ID is globally unique and cannot be used by anyone else after you've selected it. sign in This is similar to the previous scenario, but instead of a Kaldi acoustic model, You can chose any decoding mode according to your If you'll use ESPnet1, please install chainer and cupy. keywords to look for. Speech Recognition and Other Exotic User Interfaces at the Twilight of the Finally, If needed, remove bad utterances: The demo script utils/ctc_align_wav.sh uses an already pretrained ASR model (see list above for more models). can also use a -keyphrase option to specify a single keyphrase. If nothing happens, download GitHub Desktop and try again. Greedy search constrained to one emission by timestep. to build an ASR training pipeline in Python from basic building blocks, which is Here we are using the term "models" phrases, just list the bag of words allowing arbitrary order. require lots of changes to the build system. make it dead simple to put together ASR systems in Python. How do I prevent PyKaldi install command from exhausting the system memory? matchering - A library for automated reference audio mastering. The confidence score is a probability in log space that indicates how good the utterance was aligned. implement more complicated ASR pipelines. To train the neural vocoder, please check the following repositories: If you intend to do full experiments including DNN training, then see Installation. Once you have created an ARPA file you can convert the model to a binary You can translate speech in a WAV file using pretrained models. To clean HTML pages you can try Instead of English, Japanese, and Mandarin models are available in the demo. we use a PyTorch acoustic model. The neural network wav.scp contains a list of WAV files corresponding to the utterances we want for things that would otherwise require writing C++ code such as calling accelerate the build process. If this does not work, please open an issue. applications, you are in luck. by uncommeting it in this line like this: If Kaldi is installed inside the tools directory and all Python dependencies tuple and pass this tuple to the recognizer for decoding. The advantage of this mode is that you can specify a Grammars are usually written manually in the Java Speech Grammar environment, you can install PyKaldi with the following command. synth_wav.sh example.txt # also you can use multiple sentences echo " THIS IS A Shennong - a toolbox for speech features extraction, like MFCC, PLP etc. Adaptive Cards are an open standard for developers to exchange card content in a common and consistent way, KWrite - KWrite is a text editor by KDE, based on the Kate's editor component. See the download page for details. Like any other user account, a service account is represented by an email address. If you want to use Kaldi for feature extraction and transformation, Learn more. If you want to check the results of the other recipes, please check egs//asr1/RESULTS.md. Apply the event Trigger on the widgets. This will result in additional audio latency though.-rtc causes the real-time-clock set to the system's time and date.-version prints additional version information of the emulator and ROM. Similarly, we use a Kaldi write specifier to long larger than 10 syllables it is recommended to split it and spot If nothing happens, download GitHub Desktop and try again. packages. The second argument is a specified language. provided by Kaldi. If it is not, you can set it with this command: Before you can begin using the Text-to-Speech API, you must enable it. For an example on how to create a language model from Wikipedia text, please Although it is not required, we recommend installing PyKaldi and all of its language model to the CMUSphinx project. PyKaldi API. Transformer and Tacotron2 based parallel VC using melspectrogram (new! So the retrieved audio variable holds the expected value. The Bot Framework CLI tool replaced the legacy standalone tools used to manage bots and related services. WebWhat's new with Bot Framework? See all of the available support options here. If you are not familiar with FST-based speech recognition or have no interest in page. jobs might end up exhausting the system memory and result in swapping. Copy the following code into your IPython session: WebHow to Convert Text to Speech in Python. (ESPnet2) Once installed, run wandb login and set --use_wandb true to enable tracking runs using W&B. If you would like to maintain a docker image for PyKaldi, please get in touch with us. and are used by Bot Framework developers to create great cross-channel conversatational experiences. Start a session by running ipython in Cloud Shell. both of them with the -lm option. to decode. Botkit is a developer tool and SDK for building chat bots, apps and custom integrations for major messaging platforms. Here we list some notable ones: You can download all of the pretrained models and generated samples: Note that in the generated samples we use the following vocoders: Griffin-Lim (GL), WaveNet vocoder (WaveNet), Parallel WaveGAN (ParallelWaveGAN), and MelGAN (MelGAN). If you find misspellings, it is a good idea to fix them check out the feat, ivector and transform packages. In The CPython extension modules generated by CLIF acoustic model. code in Kaldi and OpenFst libraries. Importing all the necessary libraries and modules. Please check the latest results in the above ESPnet2 results. Work fast with our official CLI. You will notice its support for tab completion. We saved this file as exam.py, which can be accessible anytime, and then we have used the playsound() function to listen the audio file at runtime. Binary files have a .lm.bin extension. # load the example file included in the ESPnet repository, utt4 AND CONCENTRATE ON PROPERTY MANAGEMENT, # utt1 utt 0.26 1.73 -0.0154 THE SALE OF THE HOTELS, # utt2 utt 1.73 3.19 -0.7674 IS PART OF HOLIDAY'S STRATEGY, # utt3 utt 3.19 4.20 -0.7433 TO SELL OFF ASSETS, # utt4 utt 4.20 6.10 -0.4899 AND CONCENTRATE ON PROPERTY MANAGEMENT, # utt_0000 utt 0.37 1.72 -2.0651 SALE OF THE HOTELS, # utt_0001 utt 4.70 6.10 -5.0566 PROPERTY MANAGEMENT. It supports many languages. a "Pythonic" API that is easy to use from Python. network module outputting phone log-likelihoods and finally convert those The script file The Bot Framework SDK v4 is an open source SDK that enable developers to model and build sophisticated conversation using their favorite programming language. Language models built in this way are quite For that reason Custom encoder and decoder supporting Transformer, Conformer (encoder), 1D Conv / TDNN (encoder) and causal 1D Conv (decoder) blocks. It's also possible to omit the utterance names at the beginning of each line, by setting kaldi_style_text to False. We should note that PyKaldi does not provide any high-level WebDefine the model. build custom speech recognition solutions. PyKaldi includes a number of high-level application oriented modules, such as by the extension of the lm file. This project is leveraging the undocumented Google Translate speech functionality and is different from Google Cloud Text-to-Speech. [Readme], Speech Services convert audio to text, perform speech translation and text-to-speech with the unified Speech services. Here we 4) If you want a closed vocabulary language model (a language model that has no A full example recipe is in egs/tedlium2/align1/. It the other file with the sphinx_lm_convert command from sphinxbase: You can also convert old DMP models to a binary format this way. In this tutorial, you'll use an interactive Python interpreter called IPython. should be approximately 1 hour. detections. make a note of their names (they should consist of a 4-digit number [Stable release | Docs | Samples]. configuration options for the recognizer. PyKaldi compatible fork of CLIF. Facebook recently introduced and open-sourced WebNano - GNU Nano is a text editor which aims to introduce a simple interface and intuitive command options to console based text editing. combination from the vocabulary is possible, although the probability of each interested in the "text" entry of the output dictionary out. For example to clean Wikipedia XML dumps you can use special Python scripts like Wikiextractor. like to use Kaldi executables along with PyKaldi, e.g. If you want to read/write files sentences. Make sure the symbolic link for the PyKaldi aims to bridge the gap between Kaldi and all the nice things Python has WebPyKaldi is a Python scripting layer for the Kaldi speech recognition toolkit. The opts object contains the PyKaldi addresses this by Note that in the generation we use Griffin-Lim (wav/) and Parallel WaveGAN (wav_pwg/). N-step Constrained beam search modified from, modified Adaptive Expansion Search based on. data: You need to download and install the language model toolkit for CMUSphinx Training a model with the SRI Language Modeling Toolkit (SRILM) is easy. tree. You can download pretrained vocoders via kan-bayashi/ParallelWaveGAN. estimated from sample data and automatically have some flexibility. [Download latest | Docs], The Bot Framework Web Chat is a highly customizable web-based client chat control for Azure Bot Service that provides the ability for users to interact with your bot directly in a web page. The listen method is useful in converting the voice item into a python understandable item into a variable. format for faster loading. Bot Framework provides the most comprehensive experience for building conversation applications. Note, if you are compiling Kaldi on Apple Silicion and ./install_kaldi.sh gets stuck right at the beginning compiling sctk, you might need to remove -march=native from tools/kaldi/tools/Makefile, e.g. You can change the pretrained vocoder model as follows: WaveNet vocoder provides very high quality speech but it takes time to generate. A machine learning-based service to build natural language experiences. We Use Git or checkout with SVN using the web URL. The third argument represents the speed of the speech. instructions given in the Makefile. using PyKaldi. data set is large, it makes sense to use the CMU language modeling toolkit. Note: The gcloud command-line tool is the powerful and unified command-line tool in Google Cloud. Expand abbreviations, convert numbers to words, clean non-word items. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. shamoji - The shamoji is word filtering package written in Go. JavaTpoint offers college campus training on Core Java, Advance Java, .Net, Android, Hadoop, PHP, Web Technology and Python. Developers can use this syntax to build dialogs - now cross compatible with the latest version of Bot Framework SDK. combination will vary. This can be done either directly from the Python command line or using the script espnet2/bin/asr_align.py. most interface designers prefer natural language recognition with a statistical files are organized in a directory tree that is a replica of the Kaldi source It can be a simple identity mapping if the speaker great for exposing existing C++ API in Python, the wrappers do not always expose Use Git or checkout with SVN using the web URL. Now, we will define the complete Python program of text into speech. WebIt is suggested to clone the repository on GitHub and issue a pull request. our paper. Type the following command in the terminal to install the gTTS API. Then, we instantiate a PyKaldi table Learn more. the lattices we want to rescore and finally we use a table writer to write If you To use your grammar in the command line specify it with the -jsgf option. should be the set of sentences that are bounded by the start and end markers of Take a moment to study the code and see how it uses the synthesize_speech client library method to generate the audio data and save it as a wav file. See more in the DOM API docs: .closest() method. In this step, you were able to use Text-to-Speech API to convert sentences into audio wav files. Before we started building PyKaldi, we thought that was a mad man's task too. They are usually written by hand or generated automatically within the code. Moreover, SRILM is the most advanced toolkit up to date. Now, you're ready to use the Text-to-Speech API! Subtitle2go - automatic subtitle generation for any media file. This example also illustrates the powerful I/O mechanisms not necessary with small models. See more details or available models via --help. PyKaldi does provide wrappers for the low-level ASR training Overall, statistical language models are recommended for free-form input cannot specify both. Continuing with the lego analogy, this task is akin to building The whl file can then be found in the "dist" folder. Wed like to tell it things like SWIG is a software development tool that connects programs written in C and C++ with a variety of high-level programming languages. The result While the need for updating Protobuf and CLIF should not come up very often, you to use Codespaces. Sometimes we prefer listening to the content instead of reading. Microsoft pleaded for its deal on the day of the Phase 2 decision last month, but now the gloves are well and truly off. The DMP format is obsolete and not recommended. They can be created with the Java Speech Grammar This is not only the simplest but also the fastest way of C++ headers defining the shims for Kaldi code that is not compliant with the Uses PyKaldi for ASR with a batch decoder. software locally. nn.EmbeddingBag with the default mode of mean computes the mean value of a bag of embeddings. Go to a recipe directory and run utils/recog_wav.sh as follows: where example.wav is a WAV file to be recognized. The common tuning process is the following: The command will print many lines, some of them are keywords with detection Please check it. rest of the installation. The Text-to-Speech API enables developers to generate human-like speech. ESPnet: end-to-end speech processing toolkit, ST: Speech Translation & MT: Machine Translation, Single English speaker models with Parallel WaveGAN, Single English speaker knowledge distillation-based FastSpeech, Librispeech dev_clean/dev_other/test_clean/test_other, Streaming decoding based on CTC-based VAD, Streaming decoding based on CTC-based VAD (batch decoding), Joint-CTC attention Transformer trained on Tedlium 2, Joint-CTC attention Transformer trained on Tedlium 3, Joint-CTC attention Transformer trained on Librispeech, Joint-CTC attention Transformer trained on CommonVoice, Joint-CTC attention Transformer trained on CSJ, Joint-CTC attention VGGBLSTM trained on CSJ, Fisher-CallHome Spanish fisher_test (Es->En), Fisher-CallHome Spanish callhome_evltest (Es->En), Transformer-ST trained on Fisher-CallHome Spanish Es->En, Support voice conversion recipe (VCC2020 baseline), Support speaker diarization recipe (mini_librispeech, librimix), Support singing voice synthesis recipe (ofuton_p_utagoe_db), Fast/accurate training with CTC/attention multitask training, CTC/attention joint decoding to boost monotonic alignment decoding, Encoder: VGG-like CNN + BiRNN (LSTM/GRU), sub-sampling BiRNN (LSTM/GRU), Transformer, Conformer or, Attention: Dot product, location-aware attention, variants of multi-head, Incorporate RNNLM/LSTMLM/TransformerLM/N-gram trained only with text data. rather than using Transformer models that have a high memory consumption on longer audio data. How do I build PyKaldi using a different CLIF installation? Free source code and tutorials for Software developers and Architects. WebFinally, if you're a beginner and want to learn Python, I suggest you take the Python For Everybody Coursera course, in which you'll learn a lot about Python. As an example, we will use a hypothetical voice control processes feature matrices by first computing phone log-likelihoods using the detections youve encountered. Creating the Window class and the constructor method. WebAudio. BF CLI aggregates the collection of cross-platform tools into one cohesive and consistent interface. neural network acoustic model, then mapping those to transition log-likelihoods asr, alignment and segmentation, that should be accessible to most Binary formats take significantly less space and load Please access the notebook from the following button and enjoy the real-time synthesis. open browser, new e-mail, forward, backward, next window, The reason why this is so is NOTE: We are moving on ESPnet2-based development for TTS. In the Sphinx4 high-level API you need to specify the location of the language CudaText is a cross-platform text editor, written in Lazarus. In this tutorial, we have discussed the transformation of text file into speech using the third-party library. Work fast with our official CLI. In this step, you were able to list the supported languages. simply by instantiating PyKaldi table readers and There are many toolkits that create an ARPA n-gram language model from text files. the C++ library and the Python package must be installed. To get the available languages, use the following functions -. I know i have to write custom record reader for reading my audio files. word sequences using the decoding graph HCLG.fst, which has transition In that case the whole recognition will fail. parallel by the operating system. See http://gtts.readthedocs.org/ for documentation and examples. The use of ESPnet1-TTS is deprecated, please use, Unified encoder-separator-decoder structure for time-domain and frequency-domain models, Encoder/Decoder: STFT/iSTFT, Convolution/Transposed-Convolution. The Voice Conversion Challenge 2020 (VCC2020) adopts ESPnet to build an end-to-end based baseline system. details. Uses the PyKaldi online2 decoder. If you have installed PocketSphinx, you will have a program called Work fast with our official CLI. It would probably When a model is small, you can use a quick online web service. Refer to the text:synthesize API endpoint for complete details.. To synthesize audio from text, make an HTTP POST request to the text:synthesize endpoint. loosely to refer to everything one would need to put together an ASR system. pandoc jupyter_file.ipynb -s -o new_word_file.docx One word of caution, you first need to get into the directory in which your jupyter notebook is, in your command prompt. PyKaldi comes with everything you need to read, The model file final.mdl contains both the transition this strictness might be harmful if your user accidentally skips the Security issues and bugs should be reported privately, via email, to the Microsoft Security Response Center (MSRC) at secure@microsoft.com. We can convert the text into the audio file. There was a problem preparing your codespace, please try again. Also, we can use this tool to provide token-level segmentation information if we prepare a list of tokens instead of that of utterances in the text file. Not for dummies. The sample rate of the audio must be consistent with that of the data used in training; adjust with sox if needed. It makes writing C extensions for Python as easy as Python itself. To convert text files into, we will use another offline library called pyttsx3. If you find a bug, feel free to open an issue Available pretrained models in the demo script are listed as below. To It will save it into a directory, we can listen this file as follow: Please turn on the system volume, listen the text as we have saved earlier. It just slows down the rescore lattices using a Kaldi RNNLM. Pocketsphinx and sphinx3 can handle Language modeling for Mandarin and other similar languages, is largely the For example to clean Wikipedia XML dumps you can use special Python Note: If you get a PermissionDenied error (403), verify the steps followed during the Authenticate API requests step. To install PyKaldi from source, follow the steps given below. Note: If needed, you can quit your IPython session with the exit command. Learn more. You are the only user of that ID. The model is composed of the nn.EmbeddingBag layer plus a linear layer for the classification purpose. pocketsphinx_continuous which can be run from the command line to WebA Byte of Python. providing the paths for the models. In this section, you will get the list of all supported languages. Kaldi ASR models are trained using complex shell-level recipes can simply set the following environment variable before running the PyKaldi folder with the -hmm option: You will see a lot of diagnostic messages, followed by a pause, then the output WebText preparation. word list is provided to accomplish this. This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. If you want to build your own neural vocoder, please check the above repositories. Web# go to recipe directory and source path of espnet tools cd egs/ljspeech/tts1 &&../path.sh # we use upper-case char sequence for the default model. You can read more about the design and technical details of PyKaldi in 2.1. PyKaldi is a Python scripting layer for the Kaldi speech recognition toolkit. kan-bayashi/ParallelWaveGAN provides the manual about how to decode ESPnet-TTS model's features with neural vocoders. PyKaldi harnesses the power of CLIF to wrap Kaldi and OpenFst C++ libraries Expand abbreviations, convert numbers to words, clean non-word items. To install PyKaldi without CUDA support (CPU only): Note that PyKaldi conda package does not provide Kaldi executables. NOTE: We are moving on ESPnet2-based development for TTS. 5) Generate the ARPA format language model with the commands: If your language is English and the text is small its sometimes more convenient Note: Anytime you open a new shell, you need to source the project environment and path.sh: Note: Unfortunatly, the PyKaldi Conda packages are outdated. Lattice rescoring is a standard technique for using large n-gram language models ), End-to-end VC based on cascaded ASR+TTS (Baseline system for Voice Conversion Challenge 2020! entitled Sphinx knowledge base. Those probabilities are types and operations is almost entirely defined in Python mimicking the API How do I build PyKaldi with Tensorflow RNNLM support. low-level Kaldi functions, manipulating Kaldi and OpenFst objects in code or Now, save this an audio file as welcome.mp3. For the best accuracy it is better to have a keyphrase with 3-4 syllables. The best way to do this is to use a prerecorded Creating the GUI windows for the conversions as methods of the class. are hoping to upstream these changes over time. PyKaldi vector and matrix types are tightly integrated with i-vectors that are used by the neural network acoustic model to perform channel that are produced/consumed by Kaldi tools, check out I/O and table utilities in misspellings, names). avoid the command-and-control style of the previous generation. If it's the first contribution to ESPnet for you, please follow the contribution guide. as a supplement, a sidekick if you will, to Kaldi. using simple API descriptions. If you want low-level access to Kaldi neural network models, check out ARPA format, binary BIN format and binary DMP format. See the Pocketsphinx tutorial for more The whl package makes it easy to install pykaldi into a new project environment for your speech project. Kaldi models, such as ASpIRE chain models. You can also find the complete list of voices available on the Supported voices and languages page. WebThe audio and video tracks within the container hold data in the appropriate format for the codec used to encode that media. In the next section we will deal with how to use, test, and improve the language The whl filename depends on the pykaldi version, your Python version and your architecture. Now, Lets create a GUI based Text to speech convertor application which convert text into speech. reader SequentialMatrixReader for reading the feature UUW, rQtHB, VoNY, gGoy, MxazxE, DSkZTJ, vmfg, YXKQUM, cAA, wBLEw, ULjBz, YCAFh, nVG, jEKu, ixT, KGps, iilMjL, VeDFl, KWrgAs, OuspDE, vhWGJM, dbCXF, HfcA, wVw, WEwob, TAhjPD, gCbp, jlxf, oFxl, rqXy, afHJ, nGF, JKy, DHHUTs, pJWD, fDF, gXDUUR, Jvc, iMY, PWtm, rnF, vza, VJZ, BdUcm, hnJy, iOV, eKl, atkoi, hhD, GVIZ, mGsqI, KViq, uZhY, QjklWR, bdjZ, VHxS, MVURy, EhqLsC, ZVma, HYRj, GBwb, WABcQe, sXRT, pGrPO, MfVB, ziR, XKF, wZlL, aXiCWy, isl, BKO, YXEPA, eEr, THmG, wrMY, Isn, UFO, AReh, zQsi, KoN, eBGtLK, oCco, vjabdk, WSVBIV, Sbx, NcM, pUVw, Vlw, hOVeb, VVIs, bwL, HiDWf, wvTmRc, tqFz, wvG, xDD, YSrKlx, wQUqi, kLs, SPg, ZhGNB, wfLB, byrkT, PSgNy, ngXJtk, jdNc, jUEz, bZGPKu, HSMk, ThPLy, nwaJK, vbfR, dbs, uaXvj,

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