Sinhala Lyrics Search Engine

This is a simple lyrics search engine created using Elasticsearch for sinhala songs. The project consists of a Angular frontend and a Python Flask backend server.

Getting Started

Setting Up Elasticsearch

1. Download and run Elasticsearch.

This project was made using Elasticsearch version 7.7.1. Query formats may get changed in future versions.

2. Install ICU Analysis plugin.
3. Optionally install Kibana for below query operations.

Setting Up the Index

Alternatively, you can restore the index from the provided elasticsearch snapshot in the es_snapshots/ folder See more on snapshot and restore

1. Create an index named sinhala_lyrics_tokenized in the Elasticsearch and execute below queries.

PUT /sinhala_lyrics_tokenized
{
  "settings": {
    "index": {
      "analysis": {
        "analyzer": {
          "sinhalaAnalyzer": {
            "type": "custom",
            "tokenizer": "icu_tokenizer",
            "filter": ["edgeNgram"],
            "char_filter": ["dotFilter"]
          }
        },
        "filter": {
          "edgeNgram": {
            "type": "edge_ngram",
            "min_gram": 2,
            "max_gram": 50,
            "side": "front"
          }
        },
        "char_filter": {
          "dotFilter": {
            "type": "mapping",
            "mappings": ". => \\u0020"
          }
        }
      }
    }
  }
}

PUT sinhala_lyrics_tokenized/_mappings/
{
  "properties": {
    "artist": {
      "type": "text",
      "fields": {
        "keyword": {
          "type": "keyword",
          "ignore_above": 256
        }
      },
      "analyzer": "sinhalaAnalyzer",
      "search_analyzer": "standard"
    },
    "beat": {
      "type": "text",
      "fields": {
        "keyword": {
          "type": "keyword",
          "ignore_above": 256
        }
      }
    },
    "genre": {
      "type": "text",
      "fields": {
        "keyword": {
          "type": "keyword",
          "ignore_above": 256
        }
      },
      "analyzer": "sinhalaAnalyzer",
      "search_analyzer": "standard"
    },
    "key": {
      "type": "text",
      "fields": {
        "keyword": {
          "type": "keyword",
          "ignore_above": 256
        }
      }
    },
    "lyric": {
      "type": "text",
      "fields": {
        "keyword": {
          "type": "keyword",
          "ignore_above": 256
        }
      },
      "analyzer": "sinhalaAnalyzer",
      "search_analyzer": "standard"
    },
    "lyricWriter": {
      "type": "text",
      "fields": {
        "keyword": {
          "type": "keyword",
          "ignore_above": 256
        }
      },
      "analyzer": "sinhalaAnalyzer",
      "search_analyzer": "standard"
    },
    "musicDirector": {
      "type": "text",
      "fields": {
        "keyword": {
          "type": "keyword",
          "ignore_above": 256
        }
      },
      "analyzer": "sinhalaAnalyzer",
      "search_analyzer": "standard"
    },
    "shares": {
      "type": "long"
    },
    "songName": {
      "type": "text",
      "fields": {
        "keyword": {
          "type": "keyword",
          "ignore_above": 256
        }
      },
      "analyzer": "sinhalaAnalyzer",
      "search_analyzer": "standard"
    },
    "url": {
      "type": "text",
      "fields": {
        "keyword": {
          "type": "keyword",
          "ignore_above": 256
        }
      }
    },
    "views": {
      "type": "long"
    }
  }
}

2. Download Sinhala Lyrics Corpus and add documents to the created index using the Bulk API.

You may use Kibana/ Sense or any other option for above query operations.

Setting Up the Python Server

1. Install python and pip version 3
2. Install required python packages by running the following command in the project home directory. $ pip install -r requirements.txt
3. Download and setup SinLing. You may have to append project path to your path environment variable.
4. Configure the index name and Elasticsearch host:port details in /python-backend-server/main.py file.

index_name = 'sinhala_lyrics_tokenized'
es = Elasticsearch('localhost', port=9200)

Setting Up Angular Front-end

1. Download and install required node packages by running npm install in the /lyrics-search-engine/ directory.

Running the Project

1. Run the Elasticsearch instance.
2. Run the Python backend server by executing python main.py in the /python-backend-server/ directory.
3. Run the Angular web app by executing ng serve --open command in the /lyrics-search-engine/ directory.

Basic Usage Examples

• Search by a song name.

• Search by an artist name.

• Search by the lyric writer.

• Search for popular songs.

• Search using the English language. Searching song names and lyrics in English is not yet supported (You have to switch the language to English from the UI).

• Perform an advanced search with more options.

Additional Details

The project utilizes the below query types in Elasticsearch.

• Multi-match query with certain fields boosted
• Boolean query

Aditionally, below query options were also used.

• Terms Aggregation
• Sort

This project uses the Sinhala Tokenizer from SinLing, a language processing tool for Sinhala language.

Also, the project uses a Sinhala Stemmer from 'https://github.com/e11379dana/SinhalaStemming'.

English to Sinhala translations are done using the translate python package.