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Stars1
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LanguageJava
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Created about 10 years ago
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Updated over 9 years ago
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Repository Details
The repository holds the code in Java for various problems asked in a Software Engineering Interview for Product based companies like Facebook. Google, Amazon and Microsoft.
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AudioMLProject1
Voice Activity Detection: In this first assignment, we will create a dataset that simulates speech in every-day scenarios. We train a classifier on this dataset for distinguishing voiced from non-voiced sections, a task called voice activity detection, VAD for short. This, of course, requires a ground truth in terms of VAD annotations.Python
18
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AudioMLProject3
Emotion recognition of Speaker's Speech Data. Employ speaker detection classifiers for emotion recognition, a multiclass classification problem. Emotion Classes: Happy, Sad, Neutral, Relaxed and AngryPython
16
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AudioMLProject2
Speaker Detection: We have one target speaker whom we want to detect. The set of impostors is open, i.e., we have no prior information on the test speakers. An important part of the speaker detection pipeline is voice activity detection to filter out segments of the signal that do not contain speech.Python
7
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P2PSystemsProject
Handles call initiation, termination, call busy and waiting; Performs interaction with DHT (Distributed Hash Table) and KX (Key Exchange) modules. Generates pseudo-identities of callee, based on the DH (Diffe-Hellman) Key Exchange method and maintains session between caller and callee. Uses the RTP protocol to stream/exchange audio over the network reliably in real-time. Also performs self calling to mitigate profiling attacks.Java
6
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BagOfWordsModel
The bag-of-words model is a simplifying representation used in natural language processing and information retrieval (IR). In this model, a text (such as a sentence or a document) is represented as the bag (multiset) of its words, disregarding grammar and even word order but keeping multiplicity. Recently, the bag-of-words model has also been used for computer vision.[1] The bag-of-words model is commonly used in methods of document classification, where the (frequency of) occurrence of each word is used as a feature for training a classifier.Java
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ThriftParquetExample
This is a sample project which tests a Parquet implementation allowing writing of serialized Thrift objects into a Parquet file format. For more information refer to: www.parquet.ioJava
2
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AvroParquetExample
A project demonstrating the functionality of Avro and Parquet.Java
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