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LrcParser | Lyric LRC format file | Natural Language Processing library

 by   authorfu Java Version: Current License: Apache-2.0

 by   authorfu Java Version: Current License: Apache-2.0

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kandi X-RAY | LrcParser Summary

LrcParser is a Java library typically used in Artificial Intelligence, Natural Language Processing applications. LrcParser has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However LrcParser build file is not available. You can download it from GitHub.
#Basic Usage an introduction of LRC format can be found here. ####1. From a lyric file content to all readable lyric. [Line 1 lyrics, Line 2 lyrics, Line 3 lyrics]. ####2.More info ArrayList sentences=lyric.findAllSentences(-1,-1); System.out.println(sentences);. [{index:0|12000(Line 1 lyrics)17199}, {index:1|17200(Line 2 lyrics)21099}, {index:2|21100(Line 3 lyrics)-1}]. #####Sentence a Sentence is a class which presents a line of lyric from fromTime to toTime filled by a content and positioned by an index . ####3.ID Tags ID Tags info can be found by a HashTable<String,String> tags= lyric.getTags();. ####4. more useful methods see com.github.authorfu.lrcparser.Lyric.
Support
Support
Quality
Quality
Security
Security
License
License
Reuse
Reuse

kandi-support Support

  • LrcParser has a low active ecosystem.
  • It has 18 star(s) with 6 fork(s). There are 1 watchers for this library.
  • It had no major release in the last 12 months.
  • LrcParser has no issues reported. There are no pull requests.
  • It has a neutral sentiment in the developer community.
  • The latest version of LrcParser is current.
LrcParser Support
Best in #Natural Language Processing
Average in #Natural Language Processing
LrcParser Support
Best in #Natural Language Processing
Average in #Natural Language Processing

quality kandi Quality

  • LrcParser has 0 bugs and 0 code smells.
LrcParser Quality
Best in #Natural Language Processing
Average in #Natural Language Processing
LrcParser Quality
Best in #Natural Language Processing
Average in #Natural Language Processing

securitySecurity

  • LrcParser has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
  • LrcParser code analysis shows 0 unresolved vulnerabilities.
  • There are 0 security hotspots that need review.
LrcParser Security
Best in #Natural Language Processing
Average in #Natural Language Processing
LrcParser Security
Best in #Natural Language Processing
Average in #Natural Language Processing

license License

  • LrcParser is licensed under the Apache-2.0 License. This license is Permissive.
  • Permissive licenses have the least restrictions, and you can use them in most projects.
LrcParser License
Best in #Natural Language Processing
Average in #Natural Language Processing
LrcParser License
Best in #Natural Language Processing
Average in #Natural Language Processing

buildReuse

  • LrcParser releases are not available. You will need to build from source code and install.
  • LrcParser has no build file. You will be need to create the build yourself to build the component from source.
  • Installation instructions are not available. Examples and code snippets are available.
  • LrcParser saves you 164 person hours of effort in developing the same functionality from scratch.
  • It has 408 lines of code, 56 functions and 6 files.
  • It has medium code complexity. Code complexity directly impacts maintainability of the code.
LrcParser Reuse
Best in #Natural Language Processing
Average in #Natural Language Processing
LrcParser Reuse
Best in #Natural Language Processing
Average in #Natural Language Processing
Top functions reviewed by kandi - BETA

kandi has reviewed LrcParser and discovered the below as its top functions. This is intended to give you an instant insight into LrcParser implemented functionality, and help decide if they suit your requirements.

  • Parse a single line .
    • Find all sentences .
      • Extract time from line .
        • Organizes the list of sentences .
          • Finds a sentence .
            • Checks if is in the time interval .
              • Returns the contents of a list of strings .
                • Gets the lyric .
                  • Sets the content .
                    • Gets the time to milliseconds .

                      Get all kandi verified functions for this library.

                      Get all kandi verified functions for this library.

                      LrcParser Key Features

                      An lyric parser for Android and Java . Lyric LRC format file. Parse LRC lyric format content into a readable form.

                      Community Discussions

                      Trending Discussions on Natural Language Processing
                      • number of matches for keywords in specified categories
                      • Apple's Natural Language API returns unexpected results
                      • Tokenize text but keep compund hyphenated words together
                      • Create new boolean fields based on specific bigrams appearing in a tokenized pandas dataframe
                      • ModuleNotFoundError: No module named 'milvus'
                      • Which model/technique to use for specific sentence extraction?
                      • Assigning True/False if a token is present in a data-frame
                      • How to calculate perplexity of a sentence using huggingface masked language models?
                      • Mapping values from a dictionary's list to a string in Python
                      • What are differences between AutoModelForSequenceClassification vs AutoModel
                      Trending Discussions on Natural Language Processing

                      QUESTION

                      number of matches for keywords in specified categories

                      Asked 2022-Apr-14 at 13:32

                      For a large scale text analysis problem, I have a data frame containing words that fall into different categories, and a data frame containing a column with strings and (empty) counting columns for each category. I now want to take each individual string, check which of the defined words appear, and count them within the appropriate category.

                      As a simplified example, given the two data frames below, i want to count how many of each animal type appear in the text cell.

                      df_texts <- tibble(
                        text=c("the ape and the fox", "the tortoise and the hare", "the owl and the the 
                        grasshopper"),
                        mammals=NA,
                        reptiles=NA,
                        birds=NA,
                        insects=NA
                      )
                      
                      df_animals <- tibble(animals=c("ape", "fox", "tortoise", "hare", "owl", "grasshopper"),
                                 type=c("mammal", "mammal", "reptile", "mammal", "bird", "insect"))
                      

                      So my desired result would be:

                      df_result <- tibble(
                        text=c("the ape and the fox", "the tortoise and the hare", "the owl and the the 
                        grasshopper"),
                        mammals=c(2,1,0),
                        reptiles=c(0,1,0),
                        birds=c(0,0,1),
                        insects=c(0,0,1)
                      )
                      

                      Is there a straightforward way to achieve this keyword-matching-and-counting that would be applicable to a much larger dataset?

                      Thanks in advance!

                      ANSWER

                      Answered 2022-Apr-14 at 13:32

                      Here's a way do to it in the tidyverse. First look at whether strings in df_texts$text contain animals, then count them and sum by text and type.

                      library(tidyverse)
                      
                      cbind(df_texts[, 1], sapply(df_animals$animals, grepl, df_texts$text)) %>% 
                        pivot_longer(-text, names_to = "animals") %>% 
                        left_join(df_animals) %>% 
                        group_by(text, type) %>% 
                        summarise(sum = sum(value)) %>% 
                        pivot_wider(id_cols = text, names_from = type, values_from = sum)
                      
                        text                                   bird insect mammal reptile
                        <chr>                                 <int>  <int>  <int>   <int>
                      1 "the ape and the fox"                     0      0      2       0
                      2 "the owl and the the \n  grasshopper"     1      0      0       0
                      3 "the tortoise and the hare"               0      0      1       1
                      

                      To account for the several occurrences per text:

                      cbind(df_texts[, 1], t(sapply(df_texts$text, str_count, df_animals$animals, USE.NAMES = F))) %>% 
                        setNames(c("text", df_animals$animals)) %>% 
                        pivot_longer(-text, names_to = "animals") %>% 
                        left_join(df_animals) %>% 
                        group_by(text, type) %>% 
                        summarise(sum = sum(value)) %>% 
                        pivot_wider(id_cols = text, names_from = type, values_from = sum)
                      

                      Source https://stackoverflow.com/questions/71871613

                      Community Discussions, Code Snippets contain sources that include Stack Exchange Network

                      Vulnerabilities

                      No vulnerabilities reported

                      Install LrcParser

                      You can download it from GitHub.
                      You can use LrcParser like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the LrcParser component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .

                      Support

                      For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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